When Systems Fall Short: Employee Perspectives on Knowledge Management and Enterprise Social Networks

Introduction

In an increasingly globalised and digitalised working world, the effective use of knowledge is becoming a key success factor for companies. Knowledge management describes the systematic collection, organisation, distribution and use of knowledge within an organisation in order to promote both efficiency and innovation (Nonaka, 2007; Davenport, 1998). At the same time, modern technologies, especially Enterprise Social Networking Systems (ESNS), enable improved collaboration and knowledge sharing between employees. These systems are similar to social media, but are tailored to the specific requirements and security needs of organisations (McAfee, 2009; Leonardi, Huysman & Steinfield, 2013).

Motivation and Research Problem

Companies are increasingly using ESNS to break down communication barriers and increase the efficiency of internal processes (Levy, 2009; Paroutis, Al Saleh & Angwin, 2013). The rapid adoption of knowledge management systems (KMS) and ESNS has significantly changed the way organizations manage and distribute knowledge (Von Krogh, Ichijo & Nonaka, 2000; Turban, Liang & Wu, 2011). The focus is on the extent to which the use of such systems optimises knowledge management and how effectively it can actually contribute to the achievement of corporate goals (Chui, Miller & Roberts, 2009). Previous studies have shown that the use of ESNS offers significant benefits in the areas of knowledge management, knowledge transfer, and faster integration of new employees (McAfee, 2009; Levy, 2009).

However, despite the widespread use of these systems, their effectiveness in knowledge-intensive multinational organizations is poorly understood, particularly in terms of employee satisfaction, knowledge sharing, and collaboration across different seniority levels. Existing studies have not adequately examined how an employee’s tenure and position within an organization influences perceptions of these systems, nor have they adequately addressed the impact of systems on organizational performance. This research gap highlights the need for further research to better understand the added value and effectiveness of ESNS in such organizations (Paroutis, Al Saleh, & Angwin, 2013).

The aim of this study is to fill this gap by examining the impact and effectiveness of KMS and ESNS in a multinational professional services organization.

Research Questions

In this study, the following specific research questions will be examined:

RQ1: How does seniority in terms of length of service influence employees’ perceptions of the effectiveness of knowledge management systems (KMS) and enterprise social networking systems (ESNS)?

RQ2: To what extent do MS Teams, MS SharePoint, and OneDrive contribute to cross-functional collaboration and knowledge sharing within the organization?

RQ3: How do employees with different years of service (0–2 years, 3–5 years, 6–10 years, 10+ years) differ in their satisfaction and use of KMS and ESNS?

Research hypotheses

Based on the research questions, the following research hypotheses will be evaluated:

H1: The perceived effectiveness of knowledge management systems (KMS) and enterprise social networking systems (ESNS) varies considerably depending on the length of service of employees.

H2: The use of MS Teams, MS SharePoint, and OneDrive significantly improves knowledge sharing and collaboration between departments and regions in the organization.

H3: Employees with 3 to 10 years of service show the highest satisfaction with KMS and ESNS compared to employees with shorter or longer service.

In conclusion of this work, the most important results are summarized, and new issues are highlighted that should be examined in more detail in future studies in order to further explore the influence of ESNS on knowledge-intensive organizations.

Theoretical Background

Knowledge Management

In the business context, knowledge management is a relatively young interdisciplinary concept that focuses primarily on promoting learning and innovation (Gotcha, 1999). This practice encompasses the creation, organization, and transfer of knowledge within companies and touches upon many operational areas. Knowledge management plays a central role, especially for knowledge-based companies whose primary objective is the provision of intellectual services (Nonaka, 2007; Davenport, 1998).

The primary objective of knowledge management is to develop an organization’s intellectual capital. This refers to an organization’s ability to continually find creative and effective solutions to potential challenges (Rastogi, 2000). Rastogi (2002) describes the knowledge management nexus of a firm, which is composed of three interrelated elements: social capital (SC), human capital (HC), and knowledge management (KM). These components form a dense, dynamic, and mutually supportive network that emphasizes the interdependence of the individual elements. Without any of these components, the system as a whole could not exist (Rastogi, 2002).

By continually exploiting and maintaining this intellectual capital, knowledge-based and knowledge-centric firms are able to meet the challenges of their environment while effectively exploiting opportunities (Bontis, 1999).

Knowledge Management as a success factor for enterprises

Compared to ancient times, knowledge management is now a central success factor for modern businesses. Long-term success increasingly depends on the effective use of existing knowledge resources and the creation of new sources of knowledge that are continually adapted to changing conditions in the business environment in order to make informed decisions (Rastogi, 2000). The competitiveness of a company relies heavily on this intangible asset. Therefore, the acquisition, effective use, and continuous development of knowledge have become essential for a company’s success.

Rastogi (2000) emphasizes also that companies must cultivate and strategically use their intellectual resources to survive in a modern and dynamic economy. Similarly, Wolf (2001) argues that in today’s challenging business environment, companies must learn from their past mistakes rather than continually “reinventing the wheel”. Knowledge is considered a key asset that enables companies to overcome obstacles and effectively exploit opportunities.

Overall, it is now indisputable that knowledge plays a decisive role in positioning companies successfully against competitors and giving them a sustainable advantage in a constantly changing global economy.

Effective Knowledge Management Systems

Although the focus is often on IT infrastructure when creating knowledge management systems, various authors point out that there are other important factors to consider. The main objective of knowledge management systems is to facilitate employees’ access to knowledge and improve its use in order to increase overall company performance (Lin et al., 2008). However, Lin et al. (2008) found that few companies achieve their desired performance goals, despite significant investments in IT infrastructure. They point out that ‘increased IT investments do not necessarily lead to better business performance or better distribution of information among employees’ (Lin et al., 2008).

According to Lin et al. (2008), the success of a knowledge management system depends on the coordinated use of knowledge, which includes both people and techniques used within the organization. The focus should not be solely on a single factor such as IT infrastructure. ‘The combination of information technology and individual willingness to acquire knowledge in an organization influences the method and effectiveness of knowledge acquisition,’ add Lin et al. (2008).

Nevo (2003) points out that the lack of understanding of user needs is one of the main reasons why IT infrastructures are often unable to support effective knowledge management. Although IT tools can meet the different knowledge management needs in an organization, multiple tools must be integrated to achieve the desired results. This can affect the effectiveness of the knowledge management environment.

Overall, the success of knowledge management systems depends on both creating an environment that promotes the exchange of knowledge and expertise among employees and the use of specialized technologies (Hislop, 2005). Riege (2005) argues that the correct distribution of skilled personnel can play a central role in creating effective knowledge sharing.

Communities of Practice (CoP) as moderators and accelerators for knowledge management

The exchange and transfer of knowledge within organizations requires more than just occasional exchange opportunities: it must be systematically encouraged and ensured. The concept of Communities of Practice (CoP) offers an effective approach here. CoPs are groups of people with similar experiences who often come together spontaneously to solve specific problems or address common issues (Wenger & Snyder, 2000; Saint-Onge & Wallace, 2012). They exist parallel to the formal structure of the organization and thrive on intrinsic motivation, i.e. members participate voluntarily for their own benefit. Such communities have always existed, but modern knowledge management has formalized and systematized the concept. An important development here is the decontextualization of communities of practice, both in time and space, so that knowledge can be examined for its generalizability. Today, communities of practice are often IT-based and thus virtually organized. In multinational companies, they often cross geographical and cultural boundaries and can also impact multiple organizations in the context of corporate collaborations. Since communication within CoPs is largely informal, the exchange relies heavily on trust and loyalty. Without these foundations, especially in a climate of distrust or fear of opportunism, CoPs cannot thrive (Wenger et al., 2002). Many large companies, such as Siemens, Shell, or Novartis, have a large number of functioning communities of practice, often comprising several thousand members. In addition, there are smaller natural CoPs that form in the context of daily work. The topics covered by these groups range from deep-sea drilling to technical support or the implementation of a balanced scorecard. Another characteristic of modern CoPs is that, although often virtual, they typically meet in person at least once a year to intensify and recalibrate knowledge sharing. Communities of practice offer companies a valuable opportunity not only to share knowledge, but also to open up to new areas of activity, develop specialized skills, and disseminate best practices (Wenger & McDermott, 2002). Even if CoPs do not have a clearly defined agenda or the knowledge gained seems intangible, they contribute to improving company performance.

Despite the efforts required to maintain such groups, Lesser and Storck (2001) emphasize that managers should support CoPs by identifying potential groups that can contribute to improving the firm’s strategic capabilities. These groups should be equipped with the necessary infrastructure and evaluated using non-traditional methods such as systematic listening to testimonies.

Aspects of Measurement

Measuring knowledge in organizations is a complex task that takes into account both tacit and explicit knowledge. Nonaka (2007) in his theory of tacit and explicit knowledge refers to how knowledge can be made measurable. Tacit knowledge is the personal subjective knowledge that each employee brings to a community of practice (CoP). This knowledge is often difficult to articulate and is based on experience and intuition. In contrast, there is explicit knowledge that is created through formal processes of the organization and is measurable. According to Nonaka (2007), the transformation of tacit into explicit knowledge is crucial for organizational success, but only certain knowledge components are prioritized depending on the type of organization.

Peter Drucker (2007) argues that the purely financial evaluation of a company is not an adequate basis for measuring company performance. It does not show how communities of practice work and achieve results through the management information system on a daily basis. For this reason, companies must develop new and specific methods for measuring their performance that go beyond traditional financial metrics and take into account knowledge sharing and process optimization.

Measuring the Value Contribution of Knowledge Management Systems (KMS)

The specific value contribution of knowledge management systems (KMS) is a central aspect in the evaluation of organizational performance. KMS help to capture, share and optimize internal knowledge, but their effectiveness must be carefully measured in order to evaluate their contribution to company success. One of the main challenges in measuring the value contribution of KMS is the intangibility of knowledge. While financial metrics are immediately measurable, the influence of knowledge management is often less tangible.

Common methods for measuring the value contribution of KMS include the application of knowledge metrics that consider both qualitative and quantitative aspects. One method is the balanced scorecard, which analyzes the contribution of knowledge management to the four key dimensions – financial, customer, internal processes, and learning and growth (Kaplan & Norton, 1996). This method allows the contribution of KMS to be evaluated at both the operational and strategic levels. It measures not only the use of knowledge, but also how this knowledge contributes to increasing efficiency, productivity, and innovation in an organization.

Return on Knowledge (ROK) is another method that calculates the value contribution of KMS in terms of return on knowledge. The ROK measures the financial benefits achieved by using knowledge management strategies and systems and relates them to the investments involved (Wiig, 1997). By calculating ROK, companies can quantify the added value that KMS bring in the form of cost savings, efficiency improvements and better decision-making processes.

In addition, Firestone and McElroy (2003) suggest that the evaluation of KMS should not only be based on the processes of knowledge use, but also on knowledge production. This means that the effectiveness of a KMS should be measured by how well it supports the production of new knowledge and innovations, which in turn strengthen the competitiveness of the organization.

Methodology and Dataset

A data driven analysis as the quantitative method in the form of an online questionnaire was used to study the research questions. The questionnaire is a proven method for collecting large amounts of data in a standardized format and is particularly suitable for measuring attitudes and behaviors related to knowledge management and the use of enterprise social networking systems (ESNS) (Dillman, Smyth, & Christian, 2014). The questionnaire included a total of 24 questions aimed at capturing various aspects of knowledge management and the use of ESNS in companies. Data collection took place in July and August 2023.

Of the feedback collected, 66 fully completed questionnaires were included in the evaluation. This response rate is sufficient to conduct meaningful statistical analyses (Bryman, 2016). In order to ensure a differentiated investigation of respondents’ opinions and attitudes, different types of questions were used:

1. Likert scale: 14 questions were asked on a Likert scale to measure agreement or disagreement with certain statements at several levels. The Likert scale is a common method for measuring attitudes and beliefs in social science studies (Likert, 1932; Boone & Boone, 2012).
2. Multiple-choice questions: 9 questions offered respondents several response options from which they could choose the one that most applied to them. Multiple-choice questions are particularly useful for gathering information about behavior and preferences (DeVellis, 2017).
3. Numerical rating scale: One question used a numerical rating scale to obtain a quantitative assessment of certain factors. These scales are useful for identifying measurable differences in respondents’ ratings (Finstad, 2010).

To evaluate the collected data, IBM SPSS statistical software was used (Version 29.0.1.0), considered the industry standard for data analysis and used in many scientific studies (Field, 2013). The analyses focused on descriptive statistics, correlations, and mean comparisons to reveal relevant trends and relationships in respondents’ responses. This methodology provides a solid basis for testing the study hypotheses and obtaining valuable insights into the use and contribution to the value of knowledge management systems and ESNS in companies.

Since the questionnaire also contains company-specific and internal information, this questionnaire was not published. The author is available for further questions upon request.

Findings & Discussion

In this section, the results of the survey are presented, interpreted and discussed.

Q1, Q2: Structure of respondents

Table 1: Results for Q1 (IBM SPSS, own analysis)

Table 2: Results for Q2 (IBM SPSS, own analysis)

These results provide insights into the structure of respondents by job area and length of service, which significantly influences the use and perception of knowledge management systems (KMS).

Q1: Job area: The majority of respondents (90.9%) work in customer contact, suggesting that fast user-friendly KMS and ESNS are crucial to support the flow of information and efficiently handle customer requests. The small group of infrastructure employees (9.1%) are likely to require specialized technical information.

Q2: Length of service (tenure with the company): There are four groups of length of service: ‘1’=0-2 years of service; ‘2’=3-5 years; ‘3’=6-10 years; and ‘4’=more than 10 years of service. There is a balanced distribution between new employees (30.3% for 0-2 years) and long-term employees (31.8% for more than 10 years). New employees benefit from easily accessible explicit knowledge, while experienced employees play a key role in passing on tacit knowledge. Employees with medium length of service (3-10 years) can contribute important insights to improve KMS usage.

Discussion

The different needs of employee groups – based on field of activity and length of service – must be taken into account when designing KMS. KMS should offer both quick access to knowledge for new employees and opportunities for knowledge transfer between experienced and new employees.

Q3: Geographical origin

Table 3: Results for Q3 (IBM SPSS, own analysis)

Interpretation:

1. Regional concentration: Almost half of the respondents (47.0%) come from the GSA region (Germany, Switzerland, Austria). This over-represented group might have special requirements and expectations for the KMS and ESNS that are specific to their region and its working culture.
2. FraBeLux region (France, Belgium, Luxembourg): One third of respondents (33.3%) come from this region. This shows that there is also a strong group here that may have different requirements for KMS, especially in terms of multilingual content and regional specificities.
3. GROW region (UK, Ireland, Italy, Sweden, Finland, Norway, Netherlands): 16.7% of respondents come from this region. Here too, cultural differences and language barriers could play a role that needs to be taken into account in the knowledge management processes and systems.
4. Romania, Czech Republic and Portugal: With only 1.5% of respondents each, these regions are under-represented. Their specific requirements might have less influence in the overall analysis.

Discussion

The regional distribution of respondents shows a clear concentration on the GSA region, followed by the FraBeLux and GROW regions. For the design of knowledge management systems, it is important to consider the regional differences and specific requirements of these groups in order to provide an effective and adaptable solution. The less represented regions should also be included in the process with regard to their specific needs.

Q4: Evaluation of the correlation between hierarchy level and length of service. 

Table 4: Results for Q4 (IBM SPSS, own analysis)

Interpretation:

1. Positive correlation: The positive correlation of 0.685 shows that people who have been with the company longer are more likely to reach higher positions in the hierarchy level. This reflects a typical career pattern in which length of service correlates with promotion to higher positions.
2. Significance: Since the p-value is < 0.001, it is safe to say that the relationship between length of service and hierarchy level is not random. The result is statistically significant, which means that there is a strong basis for concluding that length of service plays an important role in hierarchy position.

Discussion:

The evaluation shows a strong and significant correlation between length of service and hierarchy level. Employees who have been with the company longer tend to reach higher positions, indicating internal promotion opportunities and career development within the company.

Q5: Evaluation of the correlation between length of service and the evaluation of the Knowledge Management System (KMS)

Table 5: Results for Q5 (IBM SPSS, own analysis)

Interpretation:

Weak negative correlation: The negative correlation coefficient (-0.185) does show a slight trend that employees who have been with the company for longer rate the KMS worse than newer employees, but this correlation is very weak.

Not significant: Since the significance value is 0.137, this is a non-significant result. This means that the correlation found is probably coincidental and no reliable statement can be made about the relationship between length of service and the evaluation of the KMS.

Discussion:

There is a weak negative but non-significant correlation between length of service and the subjective evaluation of the KMS. This suggests that length of service has no clear influence on the evaluation of the KMS.

Q6: Evaluation of the correlation between availability of knowledge within and outside the country and length of service

Table 6: Results for Q6 (IBM SPSS, own analysis)

1. Availability of knowledge within the country and outside the country:

The Pearson correlation between ‘knowledge availability in the own country’ and ‘knowledge availability outside the country’ is 0.415. The p-value is < 0.001, which means that the correlation is significant.

Interpretation: There is a moderate positive correlation between the perception of the availability of knowledge within and outside the country. This means that respondents who perceive access to knowledge within their own country as easy also tend to rate it as good for countries outside their own country. This could indicate that companies with good knowledge management ensure strong knowledge availability both within and outside the country’s borders.

2. Availability of knowledge within the country and length of service:

The Pearson correlation coefficient is 0.175, which indicates a very weak positive correlation and no significance (p = 0.159).

Interpretation: Length of service has no significant influence on how easy access to knowledge is perceived within one’s own country.

3. Availability of knowledge outside the country and length of service:

The Pearson correlation is 0.367, indicating a moderate positive correlation. The p-value is 0.002, indicating that the correlation is significant.

Interpretation: There is a moderate positive correlation between length of service and the perception of how easy it is to access knowledge outside one’s own country. This means that employees who have been with the company for longer tend to find access to knowledge outside their own country easier.

Q7: Evaluation of the correlation between length of service and the willingness to ask for information from superiors or known colleagues (same hierarchy level):

Table 7: Results for Q7 (IBM SPSS, own analysis)

1. Length of service and questions to superiors:

Interpretation: There is a moderate positive correlation (0.330) and a statistically significant positive correlation (p = 0.007) between length of service and the tendency to consult superiors for knowledge questions. This means that employees who have been with the company for longer are more likely to seek knowledge from their superiors. This could indicate that long-term employees are more likely to have established relationships with their superiors and thus show a stronger tendency to use superiors as a source of knowledge.

2. Tenure and questions to known colleagues of same level:

The Pearson correlation is 0.307 with a statistically significant positive correlation (p = 0.012).

Interpretation: There is also a moderate positive correlation between tenure and the willingness to ask for knowledge from known colleagues. Long-term employees are more likely to draw on their internal network of colleagues they know well to fill knowledge gaps. This suggests that as tenure increases, trust and interaction with familiar colleagues as sources of knowledge also increases.

3. Relationship between questions to superiors and known colleagues:

The correlation between these two variables is 0.834 with a very strong positive correlation (p < 0.001).

Interpretation: The strong positive correlation shows that employees who frequently request knowledge from superiors or partners also tend to intensively use their network of known colleagues as a source of knowledge. This indicates a general preference for requesting knowledge from people with whom employees have a certain relationship or trust.

Q8: Analysis of statistics on the availability of knowledge data sources

Figure 1: Results for Q8 (IBM SPSS, own analysis)

The figure shows the distribution of answers to the question of where knowledge documents are predominantly stored.

Private (local) MS Teams: With 25.76% of responses, this is the most common storage location. This suggests that a significant proportion of knowledge documents are stored in private hard-to-access MS Teams, indicating limited availability for other employees.

Personal laptops/OneDrive: 42.43% of knowledge documents are stored on respondents’ personal laptops or in OneDrive folders. This is another indication that a large amount of knowledge is stored decentral and private on individual devices.

In OneDrive folders that have been shared, only 7.58% of documents are stored. This shows that some knowledge is made accessible to certain groups.

Intranet and publicly accessible MS Teams (company-wide): only 24.24% of knowledge documents are publicly accessible.

Q9: Evaluation of relationship between hierarchy level and the subjective evaluation of the knowledge management system (KMS)

Table 8: Results for Q9 (IBM SPSS, own analysis)

Hierarchy level of employees is divided into six levels, with ‘1’ representing newcomers and ‘6’ long-standing employees).

The subjective rating of the KMS varies depending on the employee’s hierarchical level. While most employees rate the KMS with 4 or 5 stars, there are also some critical voices at the middle levels (especially level 3).

Q10: Evaluation of relationship between cross-competence group collaboration and length of service:

Table 9: Results for Q10 (IBM SPSS, own analysis)

Interpretation:

The assumption that the knowledge management system supports cross-group knowledge sharing is partially confirmed by the data, but there are differences in perception depending on the length of service:

1. New employees (0-2 years) perceive collaboration as difficult, indicating that the KMS may not provide sufficient support to integrate them quickly and effectively into cross-group networks.
2. Employees with 3-5 years of service show mixed experiences. The KMS could support collaboration in some cases, while in other cases it may not be sufficiently used.
3. Employees with 6-10 years also experience collaboration as moderately difficult, suggesting that further measures to optimize the KMS may be needed.
4. Long-term employees (more than 10 years) have a neutral to positive attitude towards collaboration. This shows that the KMS supports experienced employees well by enabling them to access cross-group knowledge.

Q11, 12, 13: Evaluation of satisfaction with MS Teams, MS SharePoint, and OneDrive in relation to tenure

Table 10: Results for Q11 ‘MS Teams’ (IBM SPSS, own analysis)

Table 11: Results for Q12 ‘MS SharePoint’ (IBM SPSS, own analysis)

Table 12: Results for Q13 ‘OneDrive’ (IBM SPSS, own analysis)

In this question, a detailed overview is provided of employee satisfaction with three knowledge management systems (KMS): MS Teams, MS SharePoint and OneDrive. The satisfaction is expressed in five categories and compared to tenure (in four groups).

Category: ‘Does not work effectively, replacement or re-work urgently required’: MS SharePoint is perceived as the most ineffective, especially by employees with more than 10 years of service (33.3%).

Category: ‘Is not a knowledge related tool’: OneDrive is perceived as not knowledge related by a larger proportion of respondents (especially those with 0-2 and 3-5 years of service). MS Teams and MS SharePoint are viewed by fewer employees as unsuitable for knowledge management.

Category: ‘Some improvements required’: MS SharePoint is the system where most employees see improvement needs. Employees with 0-2 years of service are particularly critical of SharePoint (65% demand improvements).

Category: ‘Works well or ok, no major changes required’: MS Teams is rated as functional by most respondents (42.4%), followed by OneDrive (34.8%). MS SharePoint performs the worst (18.2%).

Discussion

Satisfaction with the three knowledge management systems (MS Teams, MS SharePoint and OneDrive) varies greatly depending on the length of service. While MS Teams performs best overall, employees see the greatest need for improvement in MS SharePoint, especially long-term and new employees. OneDrive is also viewed critically, but less so than SharePoint.

Long-term employees and new employees have higher expectations overall and see more potential for improvement, while employees with medium length of service (3-10 years) tend to be more satisfied with the systems.

Conclusion

The present study provides empirical insight into the impact and efficiency of knowledge management systems (KMS) in practical application by knowledge workers in a professional services firm. The results show that the use and perception of KMS depends strongly on the length of service and the position of employees in the company, which leads to different results in practice. This confirms that the benefits of KMS often highlighted in the literature – such as improved knowledge distribution and increased efficiency – are not always fully realized in practical application (Nonaka, 2007; Davenport, 1998).

Key Findings

RQ1: How does seniority in terms of length of service influence employees’ perceptions of the effectiveness of KMS and ESNS?

The results show that tenure plays an important role in the perception of the effectiveness of KMS and ESNS. In particular, employees with 3 to 10 years of experience rate systems best, while new employees have difficulties integrating into systems and long-term employees tend to be dissatisfied.

RQ2: To what extent do MS Teams, MS SharePoint, and OneDrive contribute to cross-functional collaboration and knowledge sharing within the organization?

While MS Teams is considered a powerful tool for cross-departmental collaboration, MS SharePoint and OneDrive are viewed more critically. In particular, new employees did not perceive these systems as primary knowledge management tools, suggesting training gaps or a lack of onboarding.

RQ3: How do employees with different years of service (0–2 years, 3–5 years, 6–10 years, 10+ years) differ in their satisfaction and use of KMS and ESNS?

Employees with an average length of service (3–10 years) showed the greatest satisfaction and efficiency in using KMS and ESNS. New employees (0-2 years) and long-term employees (more than 10 years) were less satisfied, with new employees often complaining about a lack of integration and long-term employees complaining about a lack of flexibility of the systems.

Research Hypothesis:

H1: The perceived effectiveness of knowledge management systems (KMS) and enterprise social networking systems (ESNS) varies considerably depending on the length of service of employees.

The results of the study largely confirm this hypothesis. Employees with 3 to 10 years of service rate the systems significantly more positively than employees with shorter or longer service. This suggests that employees with medium professional experience can use systems more effectively because they are already sufficiently integrated but have not yet developed strong frustration or alienation like long-term employees.

H2: The use of MS Teams, MS SharePoint, and OneDrive significantly improves knowledge sharing and collaboration between departments and regions in the organization.

The study was only able to partially confirm this hypothesis. Most employees see MS Teams as beneficial to knowledge sharing and collaboration, while MS SharePoint and OneDrive are rated more critically. New and long-term employees in particular see potential for improvement.

H3: Employees with 3 to 10 years of service show the highest satisfaction with KMS and ESNS compared to employees with shorter or longer service.

This hypothesis was clearly confirmed. The group of employees with medium tenure rated the systems as the best on average, while new and long-term employees were more likely to express criticism and demand improvements.

Practical Implications

1. Improve training and onboarding strategies: The varying levels of usage and satisfaction rates, especially among new employees, indicate the potential to optimize training programs and onboarding processes. Quick integration into knowledge networks is essential (Wenger & Snyder, 2000), as well as communication and adoption of training programs (Riege, 2005).
2. Improved system integration for long-term employees: For long-term employees who have more complex KMS requirements, system adaptations should be considered. This can be achieved by better integrating Communities of Practice (CoPs) to strengthen informal knowledge sharing (Nonaka, 2007; Wenger & Snyder, 2000).
3. Regular system evaluation and feedback mechanisms: To ensure continuous adaptation and improvement of the KMS, companies should establish regular feedback mechanisms. This makes it possible to respond quickly to specific employee requirements and problems and to increase the efficiency of systems in view of the changing needs of the workforce (Nevo, 2003).

Limitations and Future Research Directions

As with any study, this work has specific limitations that should be considered when interpreting the results:

1. Sample size and industry specificity: The sample consists exclusively of knowledge workers in the professional services industry, which limits the generalizability of the results. Future studies should try to use a larger and more diverse sample to generalize the results to other industries.
2. Questionnaire design and data limitations: The design of the questionnaire was not optimal and did not allow for the complete testing of all possible hypotheses. A revision of the questionnaire in future studies could provide additional insights, especially regarding the interactions between different systems and the knowledge management process.
3. Further research opportunities: Future research should focus on integrating qualitative and quantitative methods to validate and further deepen the results. The focus could be on examining departmental differences or the geographical distribution of employees to understand how KMS and ESNS work in different contexts.

Summary

The present study shows that the use and efficiency of knowledge management systems depends heavily on the length of service and individual circumstances. To maximize the benefits of KMS for all employees, companies should invest in training programs, system improvements, and feedback mechanisms to meet the needs of all employee groups and promote knowledge sharing throughout the company.

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