Organizational Knowledge Management Practices and Their Impact on Organizational Focus—Assessing the Case of the Service Industry in Ghana
Kudozia Roland Yaw
Gdirst Institute, Accra, Ghana.
DOI: 10.4236/ojbm.2023.112038   PDF    HTML   XML   152 Downloads   803 Views  


This research study investigated the importance of organizational knowledge capital in service-oriented firms in Ghana. The study’s findings indicate that knowledge capital is a crucial resource for these firms and can be derived from various sources, including government regulations, customer feedback, and training programs. The study found that firms considered knowledge more valuable if it enhanced customer satisfaction and reputation rather than solely focused on developing new products and services. The study found that firms measured the impact of their knowledge based on several metrics, including revenue goals, the facilitation of learning for future efforts, and the development of new products and services. The study further suggests that knowledge asset mapping can aid organizations in properly accounting for and tracking knowledge resources, which can enhance the ability of managers to concentrate these resources on knowledge risks and opportunities. The study also found a positive correlation between organizational focus and the organization’s asset map, indicating that a variation in organizational focus may affect how knowledge asset mapping is organized. Additionally, the study found evidence suggesting that productivity increases with increased organizational knowledge, indicating the need for businesses to set up thorough knowledge management systems to compare internal organizational performance to market and consumer expectations.

Share and Cite:

Yaw, K. (2023) Organizational Knowledge Management Practices and Their Impact on Organizational Focus—Assessing the Case of the Service Industry in Ghana. Open Journal of Business and Management, 11, 704-717. doi: 10.4236/ojbm.2023.112038.

1. Introduction

Organizational knowledge capital is an important concept for knowledge-intensive organizations as it refers to the intangible value of an organization’s knowledge, relationships, learned techniques, procedures, and innovations (Chatterji & Kiran, 2022) . Knowledge capital provides companies with a comparative advantage over their competitors. Knowledge codification, which makes individual knowledge apt for sharing, dissemination, propagation, storage, and retrieval, is an essential part of organizational knowledge (Farooq, 2020) .

Measuring organizational knowledge capital is a topic that is receiving significant attention from researchers. Although the concept has existed for a long time, the term was given its name recently (Preece, 2015) . The three fundamental components of knowledge management are the process, the people, and the overall technology as applied (McIver & Wang, 2016) . The topic related to knowledge management and measurement can be identified to be new when considering the fact that it is focused on analyzing and identifying the key way in which knowledge generation can be managed (van den Berg & Kaur, 2022) . As well it can be considered in the context of the enterprise and the overall way the different employees and participants within the enterprise would be able to perform well. An organization’s knowledge assets constitute its knowledge capital and reside in many locations within and outside the organization (Kim, Watkins, & Lu, 2017) .

An organization’s knowledge assets constitute its knowledge capital and reside in many locations within and outside the organization (Beccera-Fernandez & Sabberwarl, 2015) . Therefore, a study of knowledge capital must account for intangible knowledge’s vagaries in examining how a business develops (Westeren, 2008) . Organizational knowledge assets or capital generally refer to intangible assets such as human capital, structural capital, relationships (customer and external stakeholders), processes, procedures, innovation capital, and any technologies developed or acquired to use these assets. In short, knowledge capital is an organization’s entire body of knowledge (Ramezan, 2011; Beccera-Fernandez & Sabberwarl, 2015) .

Research and literature abound on organizational knowledge capital measurement, but there needs to be more knowledge of capital management applications within Ghana’s corporate service enterprises. It remains a problem of the availability of knowledge regarding how service companies operating in Accra actually manage the knowledge capital they generate, measure it, develop their knowledge asset map and then harness these resources towards meeting the organizational focus. Existing research on the management of organizational knowledge capital by Ghanaian enterprises has been limited to sectors such as construction (Ohemeng, 2011) , industrial (Agyemang, Ngulube, & Dube, 2019; Boateng, Dzandu, & Tang, 2016) , telecommunication (Ofori, Osei, Ato-Mensah, & Affum, 2015) , Information Communication Technology (Ofori-Dwumfuo & Kommey, 2013) , and education (Dei & der Walt, 2020; Musa, 2012) .

The focus of this research is to consider the knowledge capital management practices of organizations in the service sector in Ghana, and it will explore the generation and measurement of knowledge capital, as well as linkages between the organizational knowledge asset map with the organizational focus. The research will finally consider how organizational knowledge capital drives productivity.

The research questions arising from this research aim include the following;

RQ1. How do business organizations in Accra measure the organizational knowledge capital they acquire?

RQ1aAcquisition of organizational knowledge capital by service organizations in Ghana

RQ1bMeasurement of organizational knowledge capital by service organizations in Ghana.

RQ2How is the organizational knowledge asset map for service enterprises in Ghana linked to their organizational focus?

RQ3How is organizational knowledge capital for service organizations in Ghana linked to their productivity?

2. Literature Review

The importance of knowledge capital for gaining a competitive advantage and achieving a sustainable competitive edge has been recognized by scholars (Garcia-Perez, Gheriss, & Bedford, 2019) . It is necessary for organizations to identify their knowledge assets and develop approaches to evaluate the impact of organizational knowledge capital and its activities on performance and market value (LaFayette, Curtis, Bedford, & Iyer, 2019) . Knowledge creation involves internal and external processes, and individual and collective factors, while inter-firm collaboration and a common inter-organization platform can facilitate knowledge development (Handa, Pagani, & Bedford, 2019) .

The success of knowledge activities in an organization depends on measuring and evaluating knowledge, which helps determine its worth and benefits (Garcia-Perez et al., 2019) . However, the debate over whether knowledge should be given a monetary value continues. Different models and methodologies have been presented to measure knowledge, such as Skandia Navigator and EVA/MVA, but the approach must be appropriate for the organization’s structure and operational aspects (Bedford & Sanchez, 2021) . Indicators and methods used to measure knowledge can vary within and across industries. Designing a three-dimensional knowledge measurement conversion system that is adaptable and sensitive to organizational shifts is crucial for measuring knowledge in an organization (Heidary Dahooie, Ghezel Arsalan, & Zolghadr Shojai, 2018) .

Probst’s Knowledge Management Framework identifies four methods that organizations can use to acquire and utilize knowledge, including obtaining knowledge from other firms, external stakeholders, experts, and certain products (Aljuwaiber, 2016) . However, the framework needs to include real-life examples of strategies for each of these methods. A mixed methods study by Oliva and Kotabe (2019) found that startups in Sao Paolo, Brazil utilized practices such as internal meetings, brainstorming sessions, market assessments, obtaining customer reviews, consulting mentors and experts, and partnering with other startups to manage their knowledge effectively.

Effective implementation of knowledge management practices can positively impact a company’s productivity and performance (Hussinki, Kianto, Vanhala, & Ritala, 2017) . Studies have shown that firms engaging in high levels of knowledge management practices demonstrate better performance and are able to engage in innovation. Approaches to evaluating and measuring organizational knowledge capital include direct intellectual capital, market capitalization, return on assets, and scorecard methods (Inkinen, 2016) . There are also various methods and tools for measuring organizational knowledge, such as project management and knowledge management tools and software, assessment tools for total quality management, and educational or training courses to evaluate the knowledge management capabilities of employees (Oliva & Kotabe, 2019) .

The importance of knowledge capital for organizations is widely accepted, but managing knowledge assets and resources can be challenging (Ashok et al., 2021) . A knowledge map is a useful tool for evaluating an organization’s knowledge stock, providing a graphical representation of key assets and resources and their impact on strategic direction (Carlucci, 2012) . It can also help to identify knowledge risks, such as forgetting or missing knowledge, technological risks like cybercrime, and operational risks (Sadeghi Dastaki, Afrazeh, & Mahootchi, 2022) . There are various tools available for knowledge asset mapping, including Compendium, Mind Mapping, Concept Mapping, Dialogue Mapping, and Argument Mapping. Overall, knowledge asset mapping can improve organizational focus by improving managerial awareness of existing risks of knowledge sharing and management practices (Lerro, Santarsiero, Schiuma, & Bartuseviciene, 2023) .

Organizations face several limitations when it comes to implementing organizational knowledge management practices, such as a need for more resources and employee engagement. Studies by Oliva and Kotabe (2019) and Akgün et al. found various barriers that hinder knowledge sharing practices, including inadequate time and resources, a focus on routine work, lack of trust and competition among employees, and a lack of culture and infrastructure to support knowledge management practices (Garcia-Perez, Cegarra-Navarro, Bedford, Thomas, & Wakabayashi, 2019) . These barriers can impact an organization’s ability to share knowledge, but recommendations to improve practices include reducing excessive codification of tacit knowledge and improving coherence between codified and tacit forms of data (Shekhar & Valeri, 2023) .

3. Methodology

The quantitative research approach was adopted for this research, and it drove the data collection and analysis decisions. In line with the quantitative research approach, the data was collected from respondents using the questionnaire survey. The quantitative research approach offers the advantage of targeting a larger sample population for data collection, which can increase the generalization of the results. Where there is the need for increased objectivity in the analysis and conclusions drawn, the quantitative approach is a better choice, and the findings can support greater generalizations.

The descriptive research design was selected in line with the quantitative approach, which allowed for the observation and collection of data related to the phenomenon in question. The structured research questionnaire was adopted for data collection using ordinal and nominal scaled questions modelled along the Likert-type rating, and this allowed for a comprehensive measuring of quantitative data that would validate statistical findings. The use of structured questionnaires as an instrument in this quantitative approach allowed for a large population sample to be reached with the same questions so that uniform analysis related to the objectives and hypotheses could be carried out. The questionnaire was self-designed based on the framework for managing knowledge in an organization by Probst (1998) . The distribution of questionnaire was both paper and web-based.

A purposive sampling technique was adopted to select twenty (20) service-based firms operating within the central business district of Accra. This was to ensure that the data collection properly targeted the firms providing services in the city of Accra. The total population of employees in the selected firms was around 750. A sample size of 250 participants was determined using the Table for Determining Sample Size from a Given Population by Krejcie and Morgan (1970) . The participants were eligible to complete the questionnaire if they had worked at least six months in their current firm and are over 18 years old.

Correlation analyses were utilized to examine associations between two variables in order to evaluate the study’s assumptions. The hypotheses were put to the test using the Related-Samples Wilcoxon Signed Rank Test and Spearman Correlation Coefficient. Shapiro-Wilk was also employed to check the data’s normality.

The analyses were distinguished by the determination of the central tendency (mean, median, and mode), the dispersion around the central tendency (standard deviation and range), and the distribution of responses (frequency distributions and percentage of responses), in addition to the visuals like pie charts, histograms, bar charts, and line graphs. The management members and employees of the chosen organizations took part in the study.

The questionnaire served as a design guide for the equipment used to gather data for the study. The primary factors taken into account were the respondents’ biographical information, how organizational knowledge was acquired and measured, how the asset map and organizational focus related, and how the organizational knowledge management approach affected achieving the organizational focus.

In order to conduct a literature review, understand the various presumptions underlying organizational knowledge management research practices, and address definitional issues in this study, secondary data from scholarly books, journal articles, magazines, published and unpublished papers, working papers, and some internet sources were taken into consideration.

For this study, content analysis techniques were applied to all secondary data sources. The Statistical Package for Social Sciences (SPSS) and Microsoft Excel programs were used to conduct the primary data analysis. Data was adequately cleaned, variables were meticulously tagged, and questionnaires were serialized before being imputed into SPSS for analysis. Statistical graphs and charts were produced using the pertinent frequencies, cross-tabulations, and percentage frequencies.

In order to examine organizational knowledge management and measurement among Ghanaian service firms with a base in Accra, this study employed a quantitative survey. Out of the 250 questionnaires, 210 (210) were totally filled and submitted, and the information they contained served as the foundation for the study.

4. Results

The service sector companies operating in Accra formed the target population. The firms which took part in the survey were banking, telecommunications, broadcasting, engineering services, computer software development, support and research, consumer services, freight services, and those providing services on behalf of the state. A total of 210 of the 250 surveys were successfully completed and submitted, translating to an approximate response rate of 84%. The research participants’ demographic profile includes staff from twenty (20) service-focused businesses, with 63% of them having at least four (4) years of experience in the service industry. Table 1 indicates respondents’ experience with their current firm, showing that about 78% of the respondents have been working with their current firm for at least four (4) years.

In this research, Cronbach’s alpha for the computed variables under consideration was 0.707, which is very good for internal consistency reliability. This was interpreted as the variables having relatively good internal consistency and the instrument consistently measuring the same, as per Taber (2017). This is shown in Table 2.

Table 3 shows the descriptive statistics for the variables examined in the study. The six variables’ means and standard deviations indicated that Post Acquisition Productivity Level had the highest mean (M = 4.50), followed by Organizational Knowledge Acquisition (M = 4.19). However, all variables achieved a mean score of about 4.00 on the Likert Scale from 1 - 5, signifying their level of relevance to knowledge management practices.

Findings Relative to RQ1—How do business organizations in Ghana measure the organizational knowledge capital they acquire?

Table 1. Experience with current firm.

Table 2. Reliability of computed variables.

Table 3. Descriptive statistics for the variables under investigation.

RQ1a. How do service businesses in Ghana acquire organizational knowledge capital?

This section presents findings relating to RQ1a of this study: How do businesses acquire and utilize organizational knowledge to produce capital? The respondents were required to show the extent to which their firms gained knowledge through the under-listed sources.

The statistics in Table 4 indicated a grand mean of 4.18 (4) for all the sources, which translated to “Agree” on the Likert Scale. This indicated that the sources were all relevant to the firms’ acquiring knowledge. The standard errors of the means from Table 4 were close to zero, which indicated that the sample mean was closer to the population mean.

With all respondents indicating that the sources of organizational knowledge identified in the research were relevant to service businesses in Accra, the next focus of this research was on how these firms measured the knowledge generated. The results in Table 5 showed a grand mean of 4.11 (4, High on the Likert

Table 4. Sources of organizational knowledge.

Table 5. Measurements of organizational knowledge.

Scale), which was interpreted that respondents agreed that items on the Scale were essential to the measurement of knowledge. The reliability of the Scale was 0.816.

Findings Relative to RQ2—How is an organizational asset map linked to its organizational focus?

The respondents were asked to show the extent to which they agree with the statement “Asset Mapping system is linked to our organizational focus.” From the results shown in Table 6 below, respondents agree that their firms’ knowledge asset map was linked to their organizational focus. This was demonstrated by a mean of 4.18. The standard error of the mean (0.041) was close to zero (0), which showed that the sample mean closer to the population’s true mean.

The reliability test across the eight items resulted in a Cronbach’s Alpha of 0.836. Table 7 showed a grand mean of 4.18 (4 on the Likert Scale), showing that the respondents agree with the areas that linked the organizational asset map to organizational focus. The results indicated that organizational knowledge asset maps were accordingly linked to organizational focus through the knowledge asset management systems, followed by the position of knowledge artefacts and organizational systems and structures.

The results shown in Table 8 show the Spearman correlation coefficient ρ = 0.485, indicating that a moderately positive correlation existed between Organizational Focus and Organizational Asset Map. This means that a change in Organizational Focus will likely cause a significant difference in the organizational asset map in the same direction.

Findings Relative to RQ3—How is organizational knowledge capital for service organizations in Ghana linked to their productivity

The Spearman Correlation Coefficient was therefore used to test the HP20. From

Table 6. Organizational focus and organizational knowledge map linkage.

Table 7. Areas of linkage to organizational focus.

Table 8. Results of hypothesis testing using spearman’s Rho correlation coefficient.

Table 9. Results of hypothesis testing using spearman’s Rho correlation coefficient.

the results in Table 9, the Spearman correlation coefficient ρ = 0.387 indicated that a moderate positive correlation existed between organizational productivity and organizational knowledge volume. This means that an increase in organizational productivity is likely to cause an increase in organizational knowledge volume.

5. Conclusion

This study’s main finding is that organizational knowledge capital in Ghana is a crucial resource for service-oriented firms. According to the research, these companies derived organizational knowledge from a variety of sources, including government norms and regulations, lessons learned from the creation of products and services, training and workshops, and consumer feedback, among others. According to Crespi, Criscuolo, Haskel, and Slaughter (2008) , the use of existing knowledge from inside the firm, investment in new knowledge within the firm, and use of knowledge from outside the organization are all examples of primary sources that can contribute to a growth in knowledge.

The measurement of knowledge or its impact reflects its use (ability to create capital) in an organization of knowledge within the organization, primarily in the context of the organizational focus. The measures used in the research were based on the impact or usefulness of the knowledge in the context of the organization’s activities. From the results, it was seen that firms considered knowledge acquired to be more valuable if it 1) enhanced Customer satisfaction and 2) enhanced its reputation to be trusted by partners and customers. Other metrics used by the firms included the Degree to which the project facilitated “learning” for “future efforts,” the Degree to which knowledge acquired helped in meeting revenue goals, and the Degree to which knowledge acquired facilitated the development of new products and services and the Degree to which the knowledge acquired provides a competitive advantage. This finding agrees with the study by Lebtag (2020) , which noted the importance and the need for participation in productivity measurement in the knowledge economy and knowledge management. Whereas it is well known that many organizations pursue organizational knowledge to remain competitive, the findings indicated that the firms in the service industry were more concerned about customer satisfaction and reputation than developing new products and services.

Harper (2018) of the American Productivity and Quality Center (AQPC) defines a knowledge map as a visual representation of the organization’s intellectual capital and further notes that knowledge maps aid stakeholders in finding where critical knowledge resource is, how it flows, and any barriers or gaps. Knowledge asset maps enhance the ability of managers to properly account for and track knowledge resources and the progress of the organization’s focus. In effect, asset maps assist managers in concentrating these knowledge resources on the knowledge risks that pose the greatest threat and the knowledge opportunities that promise the greatest reward.

It was determined from the results of this study that organization mapped their knowledge artefacts intending to achieve organizational focus. The findings further showed that these mappings were achieved through the capability of the Knowledge Asset management systems, the positioning of the knowledge asset, several innovative products or services by the asset, the operational goals of the firm and volume of tasks previously assigned, and the number of references or citation to the assets. The hypothesis testing results showed a moderately positive correlation between Organizational Focus and Organizational Asset Map. This indicates that a variation in the organizational focus is highly likely to affect how the knowledge asset map is organized.

The amount of organizational knowledge that the businesses had gained and their productivity needed to be compared in order to discover how the firms measured that knowledge. The findings showed a somewhat favourable association between organizational productivity and the volume of organizational knowledge. Also, there was evidence suggesting that productivity would rise with an increase in the amount of information obtained. The premise is that when an organization has a great amount of information available, it will likely be used, which will lead to knowledge capital.

It is advised that businesses in Ghana’s service industry set up thorough knowledge management databases or information systems so that internal organizational performance may be compared to current market and consumer expectations (Kane, 2017) . This will enhance the processes for applying, acquiring, and utilizing knowledge.

The objectives of knowledge management with regard to organizational focus, stakeholders, and personnel should be understood by managers. The manager will then have a better understanding of managing knowledge resources. Normally, a manager should select if the management’s goal is value management or value communication. This allows the manager to choose the methodologies for knowledge asset assessment that will be used in the knowledge management framework.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Agyemang, B. K., Ngulube, P., & Dube, L. (2019). Utilizing Knowledge Management Methods to Manage Beads-Making Indigenous Knowledge among the Krobo Communities in Ghana. South African Journal of Information Management, 21, a1008.
[2] Aljuwaiber, A. (2016). Communities of Practice as an Initiative for Knowledge Sharing in Business Organisations: A Literature Review. Journal of Knowledge Management, 20, 731-748.
[3] Ashok, M., Al Badi Al Dhaheri, M. S. M., Madan, R., & Dzandu, M. D. (2021). How to Counter Organisational Inertia to Enable Knowledge Management Practices Adoption in Public Sector Organisations. Journal of Knowledge Management, 25, 2245-2273.
[4] Beccera-Fernandez, I., & Sabberwarl, R. (2015). Knowledge Management—System and Process. Routledge.
[5] Bedford, D., & Sanchez, T. W. (2021). Networks in the Knowledge Economy. In D. Bedford, & T. W. Sanchez (Eds.), Knowledge Networks (Working Methods for Knowledge Management) (pp. 3-20). Emerald Publishing Limited.
[6] Boateng, H., Dzandu, M. D., & Tang, Y. (2016). Knowledge Sharing among Employees in Ghanaian Industries: The Role of Transformational Leadership Style and Communal Organizational Culture. Business Information Review, 33, 145-154.
[7] Carlucci, D. (2012). Assessing the Links between Knowledge Assets and Value Creation in Organizations. Measuring Business Excellence, 16, 70-82.
[8] Chatterji, N., & Kiran, R. (2022). The Influence of Human, Organizational and Relational Capital of Universities on Their Performance: A Developing Economy Perspective. Journal of Intellectual Capital.
[9] Crespi, G., Criscuolo, C., Haskel, J., & Slaughter, M. (2008). Productivity Growth, Knowledge Flows and Spillovers. National Bureau of Economic Research.
[10] Dei, D. J., & der Walt, T. B. (2020). Knowledge Management Practices in Universities: The Role of Communities of Practice. Social Sciences & Humanities Open, 2, Article ID: 100025.
[11] Farooq, R. (2020). Developing a Conceptual Framework of Knowledge Management. International Journal of Innovation Science, 11, 139-160.
[12] Garcia-Perez, A., Cegarra-Navarro, J. G., Bedford, D., Thomas, M., & Wakabayashi, S. (2019). Building Knowledge Capacity through Knowledge Capabilities. In A. Garcia-Perez, J. G. Cegarra-Navarro, D. Bedford, M. Thomas, & S. Wakabayashi (Eds.), Critical Capabilities and Competencies for Knowledge Organizations (Working Methods for Knowledge Management) (pp. 67-92). Emerald Publishing Limited.
[13] Garcia-Perez, A., Gheriss, F., & Bedford, D. (2019). Metrics for Knowledge Capital Assets. In A. Garcia-Perez, F. Gheriss, & D. Bedford (Eds.), Designing and Tracking Knowledge Management Metrics (Working Methods for Knowledge Management) (pp. 145-160). Emerald Publishing Limited.
[14] Handa, P., Pagani, J., & Bedford, D. (2019). Identifying and Categorizing Organization’s Knowledge Assets. In P. Handa, J. Pagani, & D. Bedford (Eds.), Knowledge Assets and Knowledge Audits (Working Methods for Knowledge Management) (pp. 79-104). Emerald Publishing Limited.
[15] Harper, M. (2018). 4-Step Guide to Knowledge Mapping. APQC.
[16] Heidary Dahooie, J., Ghezel Arsalan, M. R., & Zolghadr Shojai, A. (2018). A Valid and Applicable Measurement Method for Knowledge Worker Productivity. International Journal of Productivity and Performance Management, 67, 1764-1791.
[17] Hussinki, H., Kianto, A., Vanhala, M., & Ritala, P. (2017). Assessing the Universality of Knowledge Management Practices. Journal of Knowledge Management, 21, 1596-1621.
[18] Inkinen, H. (2016). Review of Empirical Research on Knowledge Management Practices and Firm Performance. Journal of Knowledge Management, 20, 230-257.
[19] Kane, G. C. (2017). The Evolutionary Implications of Social Media for Organizational Knowledge Management. Information and Organization, 27, 37-46.
[20] Kim, K., Watkins, K. E., & Lu, Z. (2017). The Impact of a Learning Organization on Performance: Focusing on Knowledge Performance and Financial Performance. European Journal of Training and Development, 41, 177-193.
[21] Krejcie, R. V., & Morgan, D. W. (1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement, 30, 607-610.
[22] LaFayette, B., Curtis, W., Bedford, D., & Iyer, S. (2019). Knowledge Capital—The Big Picture. In B. LaFayette, W. Curtis, D. Bedford, & S. Iyer (Eds.), Knowledge Economies and Knowledge Work (Working Methods for Knowledge Management) (pp. 87-104). Emerald Publishing Limited.
[23] Lebtag, L. (2020). Productivity Measurement of Knowledge Worker—An Empirical Research in a Context. Master’s Thesis, Steinbeis Hochschule of Management and Innovation (SMI).
[24] Lerro, A., Santarsiero, F., Schiuma, G., & Bartuseviciene, I. (2023). Mapping Knowledge Assets Categories for Successful Crowdfunding Strategies. European Journal of Innovation Management.
[25] McIver, D., & Wang, X. (2016). Measuring Knowledge in Organizations: A Knowledge- in-Practice Approach. Journal of Knowledge Management, 20, 637-652.
[26] Musa, A. M. (2012). Harnessing Knowledge for Institutional Advancement in Tertiary Educational Institutions. International Journal of Technology and Management Research, 1, 81-87.
[27] Ofori, D., Osei, A., Ato-Mensah, S., & Affum, E. K. (2015). Innovation and Knowledge Sharing: A New Competitive Advantage in the Mobile Telecommunication Industry in Ghana. Science Journal of Business and Management, 3, 57-163.
[28] Ofori-Dwumfuo, G. O., & Kommey, R. E. (2013). Utilization of ICT in Knowledge Management at the Ghana Volta River Authority. Current Research Journal of Social Sciences, 5, 91-102.
[29] Ohemeng, F. L. K. (2011). Institutionalizing the Performance Management System in Public Organizations in Ghana: Chasing a Mirage? Public Performance & Management Review, 34, 467-488.
[30] Oliva, F. L., & Kotabe, M. (2019). Barriers, Practices, Methods and Knowledge Management Tools in Startups. Journal of Knowledge Management, 23, 1838-1856.
[31] Preece, M. (2015). Managing Information and Knowledge in Service Industries. In M. Quaddus, & A. G. Woodside (Eds.), Sustaining Competitive Advantage via Business Intelligence, Knowledge Management, and System Dynamics. Advances in Business Marketing and Purchasing (Vol. 22B, pp. 3-154). Emerald Group Publishing Limited.
[32] Probst, G. J. (1998). Practical Knowledge Management: A Model That Works (pp. 17-30).
[33] Ramezan, M. (2011). Intellectual Capital and Organizational Organic Structure in Knowledge Society: How Are These Concepts Related? International Journal of Information Management, 31, 88-95.
[34] Sadeghi Dastaki, M., Afrazeh, A., & Mahootchi, M. (2022). A Two-Phase Decision- Making Model for Product Development Based on a Product-Oriented Knowledge Inventory Model. Journal of Knowledge Management, 26, 943-971.
[35] Shekhar, & Valeri, M. (2023). Trends in Knowledge Management Research in Small Businesses. European Business Review.
[36] van den Berg, H. A., & Kaur, V. (2022). Individual Knowledge Measurement: Organizational Knowledge Measured at the Individual Level. Journal of Knowledge Management, 26, 1409-1437.
[37] Westeren, K. I. (2008). How to Define and Measure Knowledge for the Analysis of Competitiveness. Journal of Regional Analysis and Policy, 38, 138-144.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.