&
Dissertation
DDM M.Sc. Advanced International Business Management & Marketing
The Relationship between Knowledge Management- and
Organizational Performance:
An integrative approach of qualitative and quantitative studies
Supervisor RuG: Henk Ritsema
Supervisor NUBS: Eleftherios Alamanos, Ph.D
Name: Michael J.J. Wouters
Student Number: S2687216 / B 140674738
Submission Date: 7th of December 2015
Rijksuniversiteit Groningen Faculteit voor Economie en
Bedrijfskunde
Abstract 4
Acknowledgements 5
I. List of Abbreviations 7
II. List of Figures 8
III. List of Tables 8
1. Introduction 9
2. Literature Review 11
2.1 Knowledge and the Firm: Basic Concepts 11
2.1.1 The Knowledge-Based View 12
2.1.2 The Competence-Based View 13
2.1.3 The Capability-Based Theory 14
2.2 Knowledge Management and Organizational Performance 15
2.2.1 What is Knowledge Management ? 15
2.2.2 Corporate Context of KM 17
2.2.3 Knowledge Management and Corporate Performance 19
Knowledge Management Practice and Organizational Performance 19 Enablers, Processes, and Organizational Performance 20
Knowledge Management and Innovativeness 22
2.2.4 Synthesis of Previous Studies 22
2.3 Objectives 23
2.4 An Integrative Approach 24
2.4.1 The Business Contextual View 25
2.4.1.1 Integrating KM - The BSC Approach 25
2.4.1.2 Embedding KM Into Business Perspectives 26
Financial Perspective 26
Internal Process Perspective 26
Learning and Growth Perspective 26
Customer Perspective 27
2.4.2 The Research Framework 29
3. Methodology 29
3.1 Research Setting 29
3.2 Variables and Measurement 30
3.2.1 Knowledge Management Performance 30
Knowledge Management Performance 30
Categorical KM Performance 31
3.2.2 Data Collection and Mathematical Analysis 32
3.2.3 Organizational Performance 35
Organizational Performance 35
Value Added Intellectual Capital Coefficient (VAICTM) Approach 36
3.2.4 VAIC Calculus 37
Capital Employed Efficiency (CEE) 37
Human Capital Efficiency (HCE) 38
Structural Capital Efficiency (SCE) 38
3.3 Data Analysis 40
4. Results and Discussion 41
4.1 KMP and Firm Performance 41
Categorical Improvements 42
4.2 Influential Differences of KMP 45
4.2.1 Synergy Effects 49
4.2.2 Follower, Investor, Maturer, and Performer 50
5. Conclusion 53
6. Limitations 54
Abstract
The role of knowledge and its management becomes significantly important for organizations and plays a crucial role in contributing to business performance. Various of research was conducted about the role knowledge plays in corporations. Current studies investigated how an organization´s success is influenced by mainly focusing on intermediate measures which first, capture only a minor fragment, and second do not reveal any strategical implications on how KM has to be implemented into business. Besides that, none of the studies came up with an attempt to conceptualize a method for quantifying and assessing the performance of KM and its relations to firm performance. Thus, this study is an approach to close this gab by utilizing a more generic perspective on KM and Organizational Performance. Conducting a study among 74 manufacturing companies within the automobile industry a Knowledge Management Performance Index (KMPI) was developed to assess an organizations success according to their KM performance making it comparable among the industry. Based on this index the study found that almost 60 per cent of the organizations could improve their performance through KM significantly. Viewing KM trough the lens of the Balanced Score Card the study found that KM interventions relating to improvements in the areas of internal processes and organizational learning are the main contributors for firm performance. Interestingly, financial aspects only play a subordinate role and customer related aspects are almost insignificant. Latter findings are important for managers when it comes to investment decisions in the field of KM as strategical implications can be derived.
Key words: Knowledge Management, Knowledge Performance Indicator, Value Added
Acknowledgements
This dissertation is dedicated in remembrance of:
I. List of Abbreviations
4-Q-KM Model 4 Quadrant Knowledge Management Model
BCV Business Contextual View
BPE Business Processing Environment
BPM Business Process Management
BPP Business Process Perspective
BSCA Balanced Score Card Approach
c.p. Ceteris Paribus
CA Competitive Advantage
CBT Capability Based Theory
CBV Competence Based View
CE Capital Employed
CEE Capital Employed Efficiency
CP Customer Perspective
CPS Categorical Performance Score
FP Financial Perspective
HC Human Capital
HCE Human Capital Efficiency
IC Intellectual Capital
ICE Intellectual Capital Efficiency
ICEL Intellectual Capital Efficiency Line
ISRM Industrial Standard Reference Model
KBV Knowledge Based View
KCP Knowledge Creation Process
KLC Knowledge Management Life Cycle
KM Knowledge Management
KMCI Knowledge Management Consortium International
KME Knowledge Management Environment
KMI Knowledge Management Initiatives
KMP Knowledge Management Performance
KMPI Knowledge Management Performance Indicator
KP Knowledge Processing
KPE Knowledge Processing Environment
KPI Key Performance Indicator
KRBV Knowledge Resource Based View
LGP Learning and Growth Perspective
OC Organizational Creativity
OP Organizational Performance
RBV Resource Based View
ROA Return on Assets
ROI Return on Investment
ROS Return on Stock
SC Structural Capital
SCE Structural Capital Efficiency
II. List of Figures
Fig. 1 General KM Definitions by Bhatt (2001) ……… ……… 13
Fig. 2 Conversion Process through Knowledge Management ………. 15
Fig. 3 Counts of KM, BPR, and TQM citations in written publications ……… 16
Fig. 4 Adjusted and modified three-tier Framework (McElroy & Firestone, 2005) ……. 18
Fig. 5 Summary of Research Model and Results ………. 19
Fig. 6 Research Model (Lee & Choi, 2003, p. 191) ……….. 21
Fig. 7 The research Model ……… 29
Fig. 8 Interrelation of Components of VAICTM ………. 37
Fig. 9 Summary of Empirical Findings within each Category ……….. 44
Fig.10 Interrelation between HCE and SCE ……….. 49
Fig.11 4-Q KM Evaluation Model ……… 50
III. List of Tables Tbl. 1 Summary of Sample Proxy Parameters ……….. 31
Tbl. 2 Adjustment and Definition of Performance Intervals ………. 34
Tbl. 3 Individually defined Judgement Intervals of the VAICTM ………. 39
1. Introduction
Modern world economy is characterized by fast, volatile, and high-value competition. To stay competitive, organizations have to be agile, flexible, and creative. The „pitch of modern economic warfare“ is determined by the transition from Industrial Economy to Knowledge Society where knowledge becomes the main determinant of economic growth and success (Hamel & Prahalad, 1994). The innovative nature of companies highly relies on the ability to capture, create, and implement relevant information incorporating it into their business processes, products, and services. From this point of view organizations „[…] are, and always will be, as valuable as their knowledge and ideas and, most critically, their ability to transform their knowledge and ideas into valuable and successful competencies, products and services” (Young, 2010,).
The question how corporate KM performance systematically influences companies overall success is not discussed sufficiently by current research. Studies just revealed theoretical contributions mainly based on philosophical assumptions. Empirical research only found that KM practices are directly related to various of intermediate measures of organizational performance such as customer intimacy, product leadership, and operational excellence, but no empirical linkages were made to organizational performance per se. Lee and Choi (2003) assume that „[…] as long as KM practices enhance intermediate […] performance, positive [organizational] performance will result“ (Zack, McKeen & Singh, 2009, p. 393) but provided no clear empirical evidence. However, in general this view is too narrow and neglecting that KM performs within a various set of strategic perspectives such as on customers, internal processes, organizational learning, and growth and development and that organizational performance should either be defined as a combination of structural, social, and financial aspects.
across the whole organization. This is crucial to understand as the „[…] challenge of managing knowledge in an organizational context lies in effectively [understanding and] harnessing multiple sources […]“ (Raghu & Vinze, 2005, p. 1062). KM is not just about technology, and is not just realizable through IT based solutions it is more about interconnecting a wide spectrum of contributors such as people, processes, and supportive technologies (Raghu & Vinze, 2005). In addition a theoretical introduction to the development of the preliminary research model and hypothesis will be outlined before providing conceptional knowledge of the research model and methodology presented in the third section. Section four and five will highlight and discuss the research findings revealing a clear comprehension of the outcome and its implication for prospect studies.
2. Literature Review
Over the last years knowledge management (KM) has „[…] progressed from an emergent concept to an increasingly common function in business organizations“ (Zack, McKeen & Sing, 2009, p. 392). Knowledge Management Research in a business context conducted within a number of different frames providing various of basic concepts and theories such as e.g. the cognitive framework theory (Ginsberg, 1989), the resource-based view (Connor & Prahalad, 1996), the competence-based view (Sanchez, 2001), the capability perspective (Teece et al., 1997) etc. with the purpose to increase the general understanding of the role of knowledge. This section will provide basic insights of the previously mentioned concepts. It will provide a brief understanding about how knowledge and KM in corporations, and introduces current empirical findings to get the relations to firm performance across.
2.1 Knowledge and the Firm: Basic Concepts
Corporations gently view knowledge as principle source of value creation, competitive advantages and, thus, as key driver for firm performance (Wang, Meister & Gray, 2013). To understand how knowledge can be converted into improved performance research developed three fundamental concepts.
2.1.1 The Knowledge-Based View
Over the last years the importance of a knowledge-based view of the firm (KBV) strongly emerged in the management literature (Alavi & Leidner, 2001). This perspective focuses on „the mechanism that drive relative performance and competitive advantage“ (Kalling, 2003, p. 68) and is more strategic in nature. The theory builds upon and extends the resource-based view (RBV) of organizations incorporating knowledge as ultimate and most strategically significant resource of a firm. Initially promoted by Penrose (1959) the RBV argues that organizations just improve their performance if, and only if resources are most effectively used, allocated, and sustainable managed. Barney (1991), Connor (1991), and Wernerfelt (1984) elaborated this view and claim that even these resources must be valuable, rare, and imperfectly imitable to achieve superior performance. Proponents of the KBV claim that these criteria can be applied on knowledge. E.g. Miller and Shamsie (1996) consider resources as being property- and knowledge-based. Property-based resources and assets respectively are legally controlled by a company and just contribute to firm performance until the market changes such that these resources/assets are no longer of value. Knowledge-based resources/assets in contrast are protected from imitation not legally, but because they are difficult to understand (valuable), unique (rare), and impossible to copy (imperfectly imitable). In other words it is not so much the tangible resource/asset that create competitive advantages and improve firm performance but the employment rendered by those resources, which in turn is a function of the firm´s know-how (Alavi & Leidner, 2001). The fact that through KM even these resources can be elaborated over time, knowledge-based resources/assets will never drop in value when markets change. The value of knowledge-based resources/assets will remain lifelong because knowledge content is atemporal (documentable), it matures with the time (developable), and is transferrable (sharable). The shift from RBV to a
view (KRBV), highlights the significant influence KM has on corporate performance by
which individual creation of unique and specific competitive advantages is possible.
2.1.2 The Competence-Based View
Another similar approach is the concept of the „competence-based view of the
firm“ (CBV) which rests on a resource-based thinking. According to scientific writers
companies face increasing difficulties managing knowledge as it is very complex to characterize (McElroy, 2003; Firestone & McElroy, 2005; Kelly, 2009; Dalkir, 2006, Bhatt, 2001). The main element of the CBV lies in its basic conception to the characteristic of corporate knowledge. Organizations distinguish between data, information, and knowledge which are perceived as subcomponents of corporate know-how (Kelly, 2009; Bhatt, 2001). Bhatt (2001, p. 69) provides a general definition (p.6):
In contrast to the KRBV the difficulty of the CBV is the relationship between knowledge, data, and information in know-how building processes. Bhatt (2001) states that this relation „[...] depends on the degree of […] interpretation [...]“ (Bhatt, 2001, p. 69). The complexity behind these know-how building processes lies in the recursive relation - meaning that the question whether Data, Information, and Knowledge are perceived as the same cannot be answered as it is dependent on an individual´s perception. Furthermore, a distinction between foreground and background knowledge of a company can be implemented. Referring to Bhatt (2001), foreground knowledge of a company can be perceived as explicit corporate know-how which is visible and can be articulated e.g. workflow regulations, strategic goals or business statements etc., while background knowledge of a firm is more difficult to capture and codify, as it is tacit and complex. He argues, that a significant hidden potential exists within the interconnection between foreground and background knowledge processing. He found, that these patterns of interaction are unique to a company and cannot be easily adopted by competitors. For this reason it is rather the unique coordination of interactions which lead to performance than
Fig. 1: General KM Definitions by Bhatt (2001)
Data: considered as raw facts
Information: regarded as an organized set of information
the intensity of organizational knowledge. Thus, the key lies in the sub-processes an knowledge processing outcomes of know-how creation and competence building which again is a function of managing knowledge resources. The aim of KM is to transform organizational know-how into corporate competences e.g. establishing focus, analytical and forward thinking, communication and technological skills, work cooperation etc.. To achieve this, mechanism of learning e.g. learning cycles, encompassing individual and group learning, human development, trial and error learning etc. are used by focusing on the social complexity of knowledge and knowledge sources (individuals). This view implies that organizations have to enhance and develop individual and corporate skills and competencies to achieve superior performance, which again is a function of learning and know-how building on a sub-processual level.
2.1.3 The Capability-Based Theory
The third perspective focuses on the capabilities of organizations. Within the
„Capability-Based Theory“ (CBT) companies are perceived as complex adaptive systems (McElroy,
Combining the introduced heuristic patterns the essence indicates that knowledge related resources pass through a conversion process (KM) through which a corporation is able to translate knowledge resources from various characteristics into corporate capabilities and competences visualized by fig. 2. Thus, it can be proposed that: Knowledge Management is the ultimate key process for organizational success as performance begins at the point where know-how, competencies, capabilities, and learning patterns are built. How this transformation process is theoretically explained will be discussed in the following section.
2.2 Knowledge Management and Organizational Performance
Based on the former theories this paragraph briefly discusses how this transformation process is explained by embedding KM into corporate context in order to make empirical links to firm performance in the following. This is why the nature of KM has to be controverted first.
2.2.1 What is Knowledge Management ?
Knowledge Management is not as old as the first universal programmable business computer (Z3 of Konrad Zuse, 1941) but it is quiet old. The first steps of KM where taken in the years between 1980 and 1990 when first pioneers started to develop a software system to better manage paper-based work. In contrast to other business enthusiasms, the
Knowledge Data Information Foreground Knowledge Background Knowledge Know-How Creation Know-How Creation
Competence and Capability Building through learning mechanisms Know-How Transformation
through Knowledge Management Activities Knowledge Resource Environment
field of KM emerged and matures over the years what can be visualized via a bibliometric analysis (data retrieved from Ngram Viewer). Fig 3 shows that most business enthusiasms
grow rapidly and reach a peak after about five to ten years, and then decline almost as rapidly as they grew (visualized by the dotted trend-lines). Knowledge Management in contrast looks dramatical different - it is still a growing and emerging area, constantly extending its task assignments as well. So defined Davenport (1994) Knowledge Management as „[…] the process of capturing, distributing, and effectively using knowledge.“ (cited in: Firestone & McElroy, 2011, p. 68). This definition has the nature of being simple, straightforward, and directly to the point. At this time KM was rather perceived as a process than as a management method which changed about ten years later. Karlsen & Gottschalk (2004) defined KM as „[…] method to simplify and improve the process of creating, sharing, distributing, capturing, and understanding knowledge in a company.“ (Karlsen & Gottschalk, 2004, p. 4). A more managerial character is included, highlighting creation and understanding of corporate knowledge. But what is KM today? A perhaps most frequently cited notion of KM is the definition of W. R. King. Although, the notion stems from the year 2009 it covers all relevant aspects of KM today. King states that „Knowledge Management is the planning, organizing, motivating, and controlling of
% of te rm-c itati on s of al l p u b li sh ed b ook s* -0,00005 -0,00000 0,00005 0,00010 0,00015 0,00020 0,00025 0,00030 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 R² = 0,7769 R² = 0,8308 R² = 0,9615
Knowledge Management Trendline KM Business Process Reengineering Trendline BPR Total Quality Manamagement Trendline TQM
Davenport, (1994) Karlsen&Gottschalk, (2004)
* in English published in the U.S.
W.R. King, (2009)
Fig. 3: Counts of KM, BPR, and TQM citations in written publications**
people, processes and systems in the organization to ensure that knowledge-related assets
are improved and effectively employed“ (King, 2009, p. 4). He elaborates KM as multidisciplinary method combining social and organizational issues out of a knowledge-resource-based perspective. KM represents one response to effectively manage the multidimensional relationship between normative, technological, and economical areas by „[…] bringing together people, processes, technology, strategy, structure and culture [...]“ (Kelly, 2009, p. 384). Thus, from a combined perspective KM can be defined as organizational interventions which „[…] includes individual and collective [knowledge-based] assets/[resources] that help and organization to perform […]“ (Resatsch & Faisst, 2003, p. 4) putting KM into a corporate context which will be explained next.
2.2.2 Corporate Context of KM
Referring to the Knowledge Management Consortium International (KMCI) which deals with developing Industrial Standard Reference Models (ISRM) for Knowledge Management, that companies can use as an approach to create valuable interventions in their own company, the Knowledge Management Life Cycle (KLC) describes the process from formulating a claim, capturing information, creating new knowledge towards integrating it as well as the measurements of outcomes within business procedures (KMCI is led by Joseph Firestone, Ph.D.). The central thinking of this association is based on two issues. First, organizations should shift their focus from the demand towards the supply side, which means they should foster the ability of creating their own corporate knowledge instead of employing the already existing one. Second, KMCI assumes that KM has be integrated into business and thus affects a firm on three layers visualized in fig. 4 (McElroy, 2003). It is shown that KM in a corporate context is a multilayered field. On a generic view it can be seen as incitement for organizational improvements which can be connected to the previously introduces theories:
develop an organizations capabilities to come up with an „absorptive capacity“ (Capability-Based-Theory, p.14).
- The Knowledge Processing Environment (KPE) - focuses on using these activities, tools, mechanisms, and/or processes with the aim to transform organizational know-how into corporate competences (Competence-Based-View, p. 13).
- The Business Processing Environment (BPE) - focuses on why, where, and to which scope, ideas of the KPE have to be implemented. The BP Outcomes are monitored, evaluated, and used in the BPE. This feedback mechanism ensures constant adoption and improvements to a non-static business environment
The contextual perspective visualizes how KM influences a firm´s performance on three layers each using the output of the former as input and vice versa. It is visualized that the potential of KM to generate CA comes from constant change in business processes. These outcomes should be steadily measured and evaluated in order to assure an on-going adaption process - which can be refereed to organizational learning (Argyris & Schön, 1978). Thus, these interrelations between learning and adoption are one of the main drivers for organizational success (Schulz & Jobe, 2001). Although these heuristics are quite
Knowledge Management Environment Knowledge Processing Environment Business Processing Environment Knowledge Management (KM) KM Outcomes KP Strategies KP Rules and Policies KP Infrastructure Learning Programs … Business Strategies Organizational Models Business Processes Product Strategies … Profitability Market Share Rentability Efficiency Value … Knowledge Processing (KP) KP Outcomes Business Processing (BP) BP Outcomes
logical and scientifically sound, they do not provide empirical evidence on how Knowledge Management and Organizational Performance are related. Thus, the next section will provide a brief outline of current studies in the field that are representing the general procedure when analyzing the relation between KM and Organizational Performance by emphasizing the ability to create CA which can be defined as as the ability to constantly capture, share, and implement new knowledge - or simply said create new ways of thinking.
2.2.3 Knowledge Management and Corporate Performance
Literature on the topic of competitive advantages revealed that these new ways of thinking are positively linked to organizational performance (Hall, 1993; Zack, 2007). This is not just philosophically assumed but also empirically investigated. The following studies represent the general procedure when analyzing the relation between KM and Organizational Performance
Knowledge Management Practice and Organizational Performance
Various of research in the field focused on KM influences on „intermediate measures“ of firm performance (Alavi & Leidner, 2001; Lee & Choi, 2003; Kalling, 2003; Gloet, 2006; Zack, McKeen & Singh, 2009; Kelly, 2009). E.g. Zack, McKeen and Singh (2009)
Organizational Performance KM Practices KM Practices KM Practices KM Practices Product Leadership Customer Intimacy Operational Excellence Financial Performance -0,272** -0,480*** -0,343*** -0,004 (NS)
Notes: ***p < 0.01, **p < 0.1; KM practices are reversed coded. Thus, the
negative sign represents a positive effect. NS= Not Significant
Dependent Intermediate
Variables Independent
Variables
conducted a survey among 1.500 to find out if knowledge management practices are positively related to organizational success using financial performance indicators as a proxy for each intermediate variable. In their study KM practices are defined as „observable organizational activities that relate to manage knowledge" (Zack, McKeen & Singh, 2009, p. 394) such as the ability to locate and share existing knowledge, experiment and create new knowledge, culture, the strategic value of knowledge, and learning. The authors found a direct relationship of knowledge management practices with intermediate measures of firm performance defined as: Product Leadership (Innovation, Quality), Customer Intimacy (Satisfaction, Retention), and Operational Excellence (Operating Costs, Financial Performance: ROA/ROI, Profitability) however, no relation was found to financial performance.
Although, this study gives evidence about how KM and intermediate corporate performance are related the authors only focus on KM practices. KM practices range from psychological approaches e.g. road maps, cognitive learning cards, learning histories, community yellow pages to managerial attempts such as communities of practices, knowledge sharing communities etc. No insights are given about how organizations perform in knowledge management practices and how this performance affect a firms success. In addition their definition of firm performance is a very one-sided interpretation. Authors rather focus in financial evaluation methods as proxies than on trying to capture the total business performance - a combination of social, structural, and financial aspects.
Enablers, Processes, and Organizational Performance
procedures [..]“ (Lee & Choi, 2003, p. 193) and that knowledge management play a crucial role for the organization to be creative. On the other hand they claim that KME such as culture, people, and structure may encourage or inhibit organizational knowledge management which in turn is resulting in more or less effective OC processes. They found that organizational culture variables (collaboration, trust, learning) are essential for knowledge creation processes resulting in better organizational creativity. Structural variables as formalization and t-shaped skills of employees do not affect knowledge creation, whereas centralization has a strong negative influence. In general this study reveals that a companies´ capability to be creative is positively related to organizational performance. Fig. 6 visualizes a summary of their research model.
According to this findings it generally can be stated that the better organizations perform in KCP the better their strategic knowledge management benefits. However, the authors only emphasized KM processes driving organizational creativity which again is too unilateral as there are more issues to focus on than only an creativity. Furthermore, their definition of Organizational Performance only focuses on ROI and ROS which are financial measurements used in corporate finance not reflecting the actual performance of the total business operation. - Socialization - Externalization - Combination - Internalization - Organizational
Creativity - Organizational Performance (ROS/ROA)
Knowledge Management
Intermediate Outcome Organizational Performance Knowledge Creation Process Knowledge Management Enablers Culture - Collaboration - Trust - Learning Structure - Centralization - Formalization People - T-shaped skills Information Technology - IT-Support S oc ial P er sp ec ti ve T ec h n ic al P er sp ec ti ve
Knowledge Management and Innovativeness
A further insightful study on KM analyzed the consequences of KM styles on a firm´s performance emphasizing innovativeness as proxy. López-Nicolas and Meroño-Cerdán (2011) claim that organizations only outperform competitors by being innovative. According to Tidd & Bessant (2010) innovativeness can be defined as corporate ability to internally generate and implement new ideas. An innovation can be described „[…] in terms of its nature, as an element, a new structure or administrative system, a policy, a new plan or program, a new production process, a product or service to the company why has been acquired or generated internally.“ (López-Nicolas & Meroño-Cerdán, 2011, p. 504). The authors argue that the innovation process highly depends on knowledge - mainly on tacit knowledge. The uniqueness and hidden potential of knowledge needs to be extracted and converted into explicit specific knowledge which is only possible by codifying and personalizing it. Codification Strategy means converting tacit to explicit knowledge, whereas Personalizing Strategies focus on encouraging employees to exchange experiences and ideas by developing communication processes and social network platforms, integrate them actively into corporate decision and task processes etc. From this point of view López-Nicolas and Meroño-Cerdán draw on the influence of codification and personalization on innovation and argue that each strategy enhance innovativeness which in turn contributes to organizational performance. They conducted a study among 310 companies focusing on the CEO-level. With a 80% response rate their study found that both strategies directly contribute to innovativeness but do not have a direct influence on corporate performance rather to intermediate measures.
2.2.4 Synthesis of Previous Studies
2003, p. 1). The here presented studies lack two critical issues: They do not clearly put KM into business context by incorporating it into different business related perspectives. Furthermore, the definition of organizational performance is commonly misleading. In most studies Organizational Performance is mainly defined through financial measurements parameters such as ROI, ROA, ROS etc. whereas mostly one or two are taken to represent firm performance. This is clearly creating a bias, as e.g. ROI or ROA is not an appropriate means of firm performance. Based on these lacks this study, tries to change the view on KM and its effects on Organizational Performance. Viewing KM through a business contextual lens will help to specifically link KM to a defined set of business areas to cover a wider spectrum of influence factors. Furthermore, the view on Organizational Performance will be extended incorporating social, structural, and financial measurements by emphasizing the value creation efficiency. With this approach it is possible to cover an organizations „non-financial“ performance as well e.g. the intellectuality of its staff. Thus, a model will be developed to align KM- and Organizational Performance addressing the following objectives.
2.3 Objectives
investment decisions due to the introduction or further improvements of KM one needs to convince top management. The lack of measurement methods make KM investment and improvement decisions a tough venture where many managers often loose concern. Thus, to ensure continues attention and a constant degree of Knowledge Management Interventions (KMI) it is necessary to understand the relation between KM and firm performance. Thus, the aim of this study is following:
- Find empirical evidence about the relation between KM- and OP
(emphasizing certain business perspectives) to eventually derive strategical adjustments and recommendations which might simplifying investment decisions.
- Presenting an attempt to evaluate a firms total KMP by introducing the Knowledge Management Performance Indicator (KMPI) a comparable value which can be used across firms within an industry when previous industry specific KM standards are defined. Thereby, it is possible to evaluate the KMP status of a firms and make it comparable to others.
Therefore, an integrative model is still missing which investigates these relationships based on a completely new approach which will be introduced in the following part of this paper.
2.4 An Integrative Approach
2.4.1 The Business Contextual View
Based on the thoughts of Stewart & Ruckdeschel (1997) the Business Contextual View (BCV) considers that an organization´s possibility to compete and perform depends on the knowledge of its staff, knowledge embodied in internal business processes and customer relationships. The implementation of performance measurement systems is important for CEOs as they are vital tools to influence and guide „[…] the behavior of personnel and other stakeholders in the business.“ (Aidermark & Sterner, 2003, p.3). Many organizations see KM as a means of avoiding repetition of work and mistakes, reducing duplication of effort, saving time on problem solving, enhancing cross-sectional work- and communication flows, stimulating innovation and product/service improvements, and getting closer to the customer (Fairchild, 2002). KM Literature is the opinion that superior knowledge management performance frees organizations to: operate on fewer assets, proceed faster, have higher turnovers, collect their cash faster, and have less volatility. The challenge to develop a knowledge management performance measurement system lies in the omnipresence and variation of knowledge management influences across an organization. Therefore, the proper approach for managers to indicate drivers for performance is selecting the right perspectives on business (Fairchild, 2002).
2.4.1.1 Integrating KM - The BSC Approach
documenting, and controlling a firms (KM) activities in order to find out how KM performs.
2.4.1.2 Embedding KM Into Business Perspectives
In combination with the insights of Nonaka & Takeuchi (1995), Kaplan & Norton (1996), Pulic (2000, 2008), Fairchild (2002), Aidermark & Sterner (2003), Arora (2002), Harmon (2007), and Tidd & Bessant (2010) the alignment of KM with the BSC approach can be defined as follows:
Financial Perspective
The Financial perspective can be connected to the area of Capital Employed (CE). CE describes an organizations total amount of capital used to generate/finance value creation. CE includes all assets employed in a business and has a bottom-line impact on a firm. KM contributes to a more efficient use of those assets improving profitability ratios, return on investments, decreasing costs of routine and administration work etc.. This reveals how an organizations´ KM performs in the short-run and focuses on a defined period of time.
Internal Process Perspective
The internal process perspective can be linked to issues of Business Process Management (BPM). Knowledge Processing Outcomes result in improvements that lead to faster, more transparent and productive, less bureaucratic business processes etc.. This perspective is about the internal structural and processual design of an organization - more precisely its structural capital (SC) - and measures how organizations could improve their internal performance on a long run.
Learning and Growth Perspective
describes a firm´s competences, skills, and abilities bound in the mind of its employees. The broad scope draws mainly on the socio-structural influences of KM and focuses on human beings and their development. To create value one approach of KM is to create a learning organization by changing the mindset of employees to develop firms specific competences. It can be assumed that organizations only grow when these cognitive and social processes are facilitated and only generate value if their HC is used in the best way possible - which is a function of KM.
Customer Perspective
The customer perspective points in the direction of acquiring knowledge about the customer´s needs and requirements such as quality, satisfaction, integration into business processes, lead time, and service etc. Measurements should consider how firms perform in their customer relationships. Therefore KM is relevant as through better communication processes, access to customer specific knowledge, transparency etc. the processing of customers objectives can be faster and more efficient by what stronger customer ties can be generated.
Coming from those perspectives it can generally be assume that a firm´s performance is determined by the combined performance affect of the four perspectives. Thus, it can be proposed that:
H1: The better a firm performs in KM in total, the better their corporate performance will
be.
KM improving internal processes affect an organizationals´ performance considerably more than the others or vice versa. However, interrelated categorical affects have to be considered as well. Thus, to measure the categorical contribution on firm performance one has to consider that KM influences differ across an organization. Thus, it can be stated:
H2: There is a significant difference between each categorical KMP influence on
Organizational Performance.
which is a combination of:
H2a: The overall success of an organization will be positively determined by KMP concluding in strong financial improvements c.p..
H2b: The better a firm performs in KM resulting in higher level of business process
improvements, the better the Organizations Performance c.p..
H2c: An organization´s relative success is significantly dependent on KMP leading to
corporate learning and growth improvements c.p..
H2d: The better a corporation performs in managing customer related knowledge,
the better their relative overall performance c.p..
Based on this assumptions, the influence of KMP on a firm´s performance is assumed to be explained as:
(1)
with:
Y = Firm Performance (dependent) bn = Coefficient of Categorical Performance a = Intercept
2.4.2 The Research Framework
Coming from these thoughts the following research framework can be developed visualized in fig. 7. It illustrates that the influence of KMP can be analyzed by a two-layer-approach. Layer one - continues green line - represents the proposition of H1 and reflects
my assumption that KMPI contributes to organizational success in general. More specific, layer two - dotted line - stands for H2 and its underlying assumptions H2a-d. It is assumed
that the overall corporate performance is determined by the KMP of each category in different ways. As discussed it will be assumed that, general KMP is a combining construct consisting out of each categorical performances. The purpose is to find if and how organizational performance is determined by each category under the assumption of H1.
The, black arrows indicates that KMPI is the transformed sum score of the categorical performance coefficients, and represent only the calculation flow.
3. Methodology 3.1 Research Setting
The model shown in fig. 7 is empirically tested through a survey concentrating on the upper management level. The aim is to receive single answers representing the KM status of a firm. Thus, the executive level of the management was used as target group as answers from upper management level are most representative for firm level data in this field. To
KMPI* Financial Perspective Internal Process Perspective Learning and Growth Perspective Customer Perspective Organizational Performance H2a H2d H2c H2b H1
* Knowledge Management Performance Indicator
collect data a survey was conducted among inter- and multinational companies within the manufacturing sector. Through shorter product life-cycles and high competition the manufacturing industry represents steadily changing business and reflects the significant needs of knowledge due to high pace of technological and product related innovations. For this reason it provides a profound environment to get representative firm level data on KM and its contributions on firm performance. To make sure to gain single company data the questionnaire was send to upper management representatives of 536 companies, partly through telephonic and newsletter support. The companies were selected based on data provided by the german automobile union. The questionnaire was only send under the premise that these organizations implemented KM already in total, 94 questionnaires out of 536 were returned (a 17,5% response rate, which was higher than expected) whereof 20 were eliminated due to incomplete data. Thus, the final sample contains firm-level data of 74 companies.
3.2 Variables and Measurement
The following parts will explain which variables were used in the study, how they are defined and how data was collected to explain how proxy parameters for corporate and knowledge management performance were developed in order to test the research framework, its hypotheses, and underlying assumptions.
3.2.1 Knowledge Management Performance
Knowledge Management Performance
processes. For this reason KM related outcomes result in a variety of business related results in line with the business contextual view presented on page 25. In order to try to cover most relevant aspects of business operations this study draws on a more results-oriented focus to KMP. Considering that, and to align it with the already presented theories KMP describes how effective a corporation uses its knowledge related assets/resources (KRBV) in order to derive business related capabilities (CBV) to develop strong, unique, and corporate specific competences (CBT). Thus, in this paper KMP will be determined as „the positive or negative affect (change) on defined business operating standards when accomplishing a given task under the support of KM resulting in social, structural, and technical capabilities and competencies “.
Categorical KM Performance
Using the BSC approach as structural fundament, this attempt tries to quantify an organizations KMP by resting upon pre-post comparison when aligning KM outcomes to the, as previously mentioned, business perspectives. To measure KMP in these areas categoric specific KPIs have to be developed trying to catch the bigger picture of business. The „change effect“ of these specific KPIs determines the categorical knowledge management performance score (CPS) a coefficient used as proxy for categorical KMP. When developing those proxies one has to notice that KM influences can be of various characteristics e.g. technical, financial, or social. For this reason, those proxies are distinguished into soft and hard parameters which is an attempt to quantify rational and emotional aspects when measuring performance. Soft parameters (emotional aspects) cover socio-psychological and structural issues whereas hard parameters (rational aspects) are linked to technical and financial. Mainly based on McElroy (2003), Lee & Choi (2003), Ragab & Arisha (2013), and Gloet (2006) proxy parameters are developed visualized in table 1.
Table. 1: Summary of Sample Proxy Parameters
Category Soft Parameters Hard Parameters
Financial Perspective
Profitability Ratios; ROI; ROA; NPV; Labour and Administration Costs; Waste Production Costs; Reduction of Raw Material Costs; Time and Cost Savings of Routine Work
Table. 1: Summary of Sample Proxy Parameters
This approach is necessary as an unilateral focus e.g. only on rational aspects might bias the outcome as the multi-complexity of an organization´s process influences is not covered sufficiently.
The Knowledge Management Performance Indicator (KMPI)
To measure an organizations ability to manage its knowledge related resources in the best way possible the synergetic effect of the categorical performances determines the overall KMP of a firm. This will be reflected in the so called Knowledge Management Performance Indicator (KMPI) a coefficient used as a proxy for a firm´s overall KMP. This coefficient indicates how effective a corporation manages its knowledge related resources to derive effective capabilities in order to develop unique competencies. KMPI reflects the insights of the CBV and CBT. The higher KMPI, the better a firms KM efficiency. How KMPI is calculated and interpreted will be discussed in the following section.
3.2.2 Data Collection and Mathematical Analysis
To collect firm level data the questionnaire was divided into four main areas in line with the perspectives of the BSC. For each area the specific proxy parameters for KMP were prompted (introduced in table 1). The aim of the questionnaire was to find out if
Learning and Growth Perspective
Employee motivation; Involvement; Improved Intellectual Competences; Personal Development; Increased Target-Performance Comparisons; Increased Number of Learning Groups;
Increased Number of Patent Registrations and R&D Projects; Increased Number of Best Practices
Internal Business Process Perspective
Reduce Redundancies; Reuse internal Knowledge; Reduce Bureaucracy; Improve Process transparency; Improved cross sectional workflow
Reduce cycle and waiting time of Processes; Reduction of Error rates; Increased Prodctivity
Customer Perspective
Mutual Benefits; Increased Satisfaction; Improved Communication; Increased quality; Increased Customer Integration
Reduced Time to React; Reduced repeated calls and end-to-end call length; Increased service/product offer
Table. 1: Summary of Sample Proxy Parameters
Soft Parameters Hard Parameters
Table. 1: Summary of Sample Proxy Parameters
Category
organizations could change certain business aspects after implementing KM. These proxies were prompted with dichotomous questions. This type of questions was used as it fits best to ask whether improvements happened or not thus, simplifying further analysis without divagating too much from business contextual implication. The aim of this approach is the determination of the above mentioned categorical knowledge management performance score (CPS) reflecting an organizations categorical performance. CPS is defined as:
(2)
with:
j = Category
i = Number of KPI (Proxy Parameter)
CPSj = Categorical Performance Score of Category j
KPIij = Key Performance Indicator (Proxy) i of category j
Drawing on whether organizations could improve certain business aspects, to calculate the CPS each positive answer was scored with one, each negative with zero points. In the end a ranking scale ranging from CPS 0 to 5 index points could be developed for each perspective with: 0 = low and 5 = successful categorical KMP compared to a grading scale. As stated a firm´s overall KMP is defined as the synergetic effect of the performances of all categories. Thus, the total KMP of an organization is assumed to be the aggregate sum the CPS and therefore ranges from0 to 20 index points (0 = low KMP; 10 = medium KMP; 20 = successful KMP). KMP is defined as:
(3)
with:
j = Category
To receive a more appropriate visualization and to align KMPI with class levels of the VAICTM (explained later on) the scale from 0 - 20 index points has to be transformed to 0 -
5 index points by taking the average. Thus, KMPI is determined as:
(4)
with:
j = Category
n = Number of Categories
KMPI = Knowledge Management Performance Index
As stated KMPI measures the total KMP of a firm. The transformed index ranges from KMPI 0 to 5 index points (0 = low performance; 5 = successful performance), where the threshold from „relatively good KM“ to „good KM“ performance is at 2,5 index points and can be compared to a grading scale. At this level firms reach min. 50% of the improvements through KM in this model. These intervals were chosen on an individual evaluation basis so that KMPI can be compared with a grading scheme at e.g. high school, assessing an organizations KMP through a lens of the KRBV. Table 2 shows the defined intervals. Each category count one quarter of the total scores of the transformed KMP =
Table 2: Adjustment and Definition of Performance Intervals
Judgement KMP KMPItransformed
Low Performance
(KM is not effectively employed, weak use of knowledge related resources, low absorptive capacity, and reuse of existing knowledge, low knowledge creation and competence building)
0 < KMP ≥ 5 0 < KMAPIaveraged ≥ 1,25
Relatively Good Performance
(KM is relatively good employed but not used effectively enough, relatively good absorptive capacity but weak competence building, capabilities are not sufficiently used and developed)
5 < KMP ≥ 10 1,25 < KMAPIaveraged ≥ 2,5
Good Performance
(KM is good employed, efficiently used, and effectively embedded, good absorptive capacity and knowledge creation, capabilities are well used and competences good developed
10 < KMP ≥ 15 2,5 < KMAPIaveraged ≥ 3,75
Succesful Performance
(KM is successfully employed and integrated; manage to deal with knowledge related assets most effectively;high absorptive capacity and competence building, new knowledge is effectively created by successfully using the generated capabilities potential
15 < KMP ≥ 20 3,75 < KMAPIaveraged ≥ 5
KMPItransformed as max. four categories are available. Organizations receiving e.g. only 5
out of 20 possible KMP scores will receive 1,25 transformed index points (KMPItransformed =
5/4 = 1,25) and fall in the interval of „low performance“ whereas firms that e.g. receive 15 KMP scores receive transformed 3,75 index points (KMPItransformed= 15/4 = 3,75) and will
fall in the interval of „good performance“. Of course this attempt is somewhat constrained as it assumes 100% KMP on a KMPItransformed index level of 5 and low KMP on a 0 level
which is indeed „pseudo-realistic“ as it is based on a subjective assumption. This has to be done as otherwise no interoperation is possible.
The here presented coefficients (CPS; KMPI) will be used in further data analysis. In the next section of this part it will be described how the variable Organizational Performance is described and calculated in this study.
3.2.3 Organizational Performance
Organizational Performance
CEOs have to be aware that the importance of intangibles increased significantly which is referred to Intellectual Capital (IC) (Vakilifard & Rasouli, 2013). Intellectual Capital consists of an organization´s abilities, competences, patents, processes, employee´s skills, technologies, information about customers and suppliers etc. (Stewart, 1997). Thus, neoclassical performance measurement only cover a minor fragment of the big picture. It would be helpful for CEOs to recognize the most influential elements of IC on organizational performance to gain a clearer understanding and better manage corporate capabilities. Drawing on IC would CEOs help to identify which models and indicators best predict organizational performance (Vakilifard & Rasouli, 2013; Nazari & Herremanns, 2007). Thus, using a generic view on firm performance this stud will draw on the Value Added Intellectual Coefficient (VAICTM). This approach tries to measure organizational
performance considering intangible and tangible input factors of business operations.
Value Added Intellectual Capital Coefficient (VAICTM) Approach
First introduced by Pulic (2000) the VAICTM is an analytical method to measure corporate
performance drawing on the total value creation efficiency of a company. The VAICTM was
designed to provide a tool to measure the efficiency of two main input factors corporation use for business operations: structural capital which incorporates physical and financial resources and human capital which incorporates intellectual and knowledge based resources (Pulic, 2000, 2008; Van der Zahn et al. 2004). These assumptions are also in line with the KRBV on a firm and the findings of Miller and Shamsie (1996) (Knowledge based resources/Property based resources introduced on p. 12). The VAICTM Approach of
Pulic tries to measure the „Intellectual Ability“ of organizations or simply said the the Value Adding Possibilities of organizations. The purpose of Pulic´s VAICTM is not to
3.2.4 VAIC Calculus
To calculate an performance efficiency coefficient the VAICTM model of Pulic is the
aggregate sum of Capital Employed Efficiency (CEE) and Intellectual Capital
Efficiency (ICE) (a compound of Structural Capital Efficiency (SCE) and Human Capital Efficiency (HCE)). Based on Stahle, Stahle & Aho (2011) and Iazzolino & Laise (2013) fig. 8 visualizes the interrelation of the sub-components of the VAICTM.
Capital Employed Efficiency (CEE)
Capital Employed (CE) represents the capital investment which is needed for business operations. This is presented as stocks, shares, and long-term liabilities, or simply, fixed assets plus working capital, respectively. The CEE describes the ratio of Value Added (VA) and Capital Employed (CE) and indicates how much Value Added is generated by utilizing a certain amount of CE. CEE is defined as:
(5)
with:
VA = Gross Income - Operating Expenses (excluding personal costs) CE = Fixed Assets - Working Capital
Structural Capital
Value Added Intellectual Capital
Human Capital Efficiency (HCE)
Human Capital (HC) of an organization represents all personal expenses and is viewed as investment costs. HCE describes the ratio of invested personal expenses (HC) and VA. This coefficient indicates „[…] how [effectively] management utilized the existing potential in the [human] resources employed in creating value.“ (Vakillifard & Rasouli, 2013, p. 33). HCE is defines as:
(6)
with:
VA = Gross Income - Operating Expenses (excluding personal costs) HC = Human Capital (Personnel Expenditure)
Structural Capital Efficiency (SCE)
Structural Capital (SC) measures all processes and structures a company has to provide within their boundaries making business operation viable. SC is the supportive infrastructure necessary for a firm to function. It is in the property of an organizations and remains even when employees leave. (Johnson, 1999). Thus, SC can be explained as the amount of value generated without taking human resources into account determined as Value Added minus Personal Expenditures (Vakillifard & Rasouli, 2013, Iazzolino & Laise, 2013, Pulic, 2000). The SCE represents the ratio between SC and VA and indicates how efficient a corporates structural capital was used in value generation.
(7)
with:
To receive at the value creation efficiency of the total firm the remaining CEE has to be added to incorporate the financial efficiency as well and determines the VAICTM as
mentioned at the beginning of this part visualized in fig. 8.
(8)
with:
ICE = HCE + SCE CEE = CE/V
The VAICTM Index normally ranges from -∞ to +∞. However, in general this coefficient
mainly represents a comparison value between organizations. A higher VAICTM implies
higher value creation efficiency. The index points have to be used as reference values. Thus, the performance thresholds and intervals have to be individually adjusted to the sample in order to interpret it (Vakillifard & Rasouli, 2013, Iazzolino & Laise, 2013, Pulic, 2000). In the data VAICTM values range from lowest performer .15 to highest performer
5,45 index points. For this reason it is possible to transform the VIACTM range and align it
with the intervals of KMPI for interpretation purposes shown in table 3. Therefore, VAICTM will range from 0 ≥ x to 5 ≥ x where 2,5 index points is defined as threshold from
„relatively good“ to „good performance“ in line with the intervals of KMPI. To collect the
Table 3: Individually defined Judgement Intervals of the VAICTM
Judgement VAICTM
Worse performance (much worrying; edge of survival)
(organizations show negative HCE,SCE, and CEE, no VA, very high personal expenditure, gross income cannot cover operating expenses)
0
Low performance (worrying)
(organizations show low HCE, SCE, and CEE due to low value added. Value creation is almost not possible as gross income only just covers operating expenses, High personal/structural costs cannot be covered by VA)
> 0 x ≤ 1,25
Relatively good performance
(organizations show relatively good HCE, SCE, and CEE values due to sufficient value added.Value creation is possible as gross income sufficiently exceeds operating expenses)
> 1,25 x ≤ 2,5 Good performance
(organizations show high HCE, SCE, and CEE due to low costs and high value added. Good value creation as gross income sufficiently covers operating expenses)
> 2,5 x ≤ 3,75
Successful performance
(organizations show high HCE, SCE, and CEE values.Very high Value Added and low operating expenses and HC costs. Successful Value creation, gross income sufficiently covers operating costs)
data needed for calculating the VAICTM the necessary figures were drawn from the latest
published annual reports of the participating companies.
3.3 Data Analysis
The model shown in fig. 7 will be tested on a two step approach. First, it will be analyzed if there is a positive relation between firms overall KM- and Firm Performance testing the assumptions of H1 by using KMPI and VAICTM as performance proxies. Second, (under the
assumptions of H1) it will be investigated if there is a significant difference in the influence
on corporate performance across the strategical perspectives of a firm, testing the assumptions of H2 and its sub-hypothesis H2a-d. The procedure of combining (mixing)
different statistical analysis is recommended to use in order to „double check“ (confirm) the results. Fahrmeir, Künstler, Pigeot & Tutz (2010) recommend to this method be appropriate in modeling, especially when trying to reduce insecurity predicting a more reliably result if the outcomes do not significantly differ. In general the model will be tested by using the method of linear correlation and multiple regression (stepwise) to find evidence if there is a positive linear relationship between the predicting variables and VAICTM. Therefore a monotonic relationship between the variables is assumed, meaning
that if one variable increases the other will increase as well or vice versa.
In the second step it will be investigated if a correlation between the categorical variables and organizational performance exists using CPSj and VAICTM as proxies. The
purpose of this step is to investigating if a positive relation between the categories and firm performance exists and if so if this influence differs between the variable in order to find out which categories contribute most to firm performance. The aim is to derive a tendency which areas are more or less important when fostering KMP through investments.
The variables were first tested on normal distribution, homoscedacity, autocorrelation, and multicollinearity in order to find out if they might violate any assumptions for OLS (multi) regression and correlation analysis. SPSS was used to conduct statistical testing providing the following descriptive and analytical results.
4. Results and Discussion 4.1 KMP and Firm Performance
Drawing on the relation between KM- and Organizational Performance, results show a statistical significant correlation between KMPI and VAICTM with Kendall´s tau-b = .669
and Spearman´s rho = .839, at p-level p<.01 (1-tailed). Linear regression indicates that a positive linear relationship between KMPI and VAICTM exists (r = .821) statistically
significant at ANOVA F(1,72) = 149,402, p<.001. Results show that the independent variable (KMPI) accounts for 67,4 per cent (R2 = .674) of the variability in the dependent
variable (VAICTM) with 𝛽 = R =.821. From those findings one might draw the conclusion
that indeed a firms overall knowledge management contributes positively to firm performance. These results imply that as knowledge management performance generally increases so do corporate performance as well thus contributing H1.
The findings are also in line with the descriptive results of the sample. As explained the KMAPItransformedranges from min 0 to max 5 index points whereof 2,5 is defined as
effectively embedded. These companies tend to posses a good „absorptive capacity“ and have a better knowledge creation ability, utilize their corporate capabilities relatively better to develop, use, and employ corporate specific competences. Classified data indicates that 63,5% of the sample performs at least in the „good performance“ range, whereof 24,23% perform „successful“ in its knowledge management activities showing the most successful employed KM. Those firms manage to deal with knowledge related assets most effectively tend to have a high competence building, and knowledge is effectively created by using the corporate´s capability-potential. The remaining organizations show only „relatively good“ performance in their KM (36,5%) implying that those organizations still have to improve. Drawing on organizational performance, data indicates that firms reached a VAICTMmean of
2,6135 implying that most organizations have an average value creation efficiency through knowledge related and knowledge supporting resources meaning that those organizations show relatively high HCE, SCE, and CEE due high value added. Chi-Square-tests reveal that more than half of the most successful organizations perform highest in their KMAs, whereas 70% of underperforming organizations show only „relatively“ good knowledge management performance - significant at 𝜒2 = 53.738, df = 6,p<.001.
Categorical Improvements
Drawing on the four strategical perspectives presented in the „integrative approach“ of the model, deeper analysis reveals that on average 66,58% of the organizations could significantly improve their business processes whereof more than 45% could improve in all five sub-parameters implying that through KM most companies could enhance their performance on a long run. According to the data these organizations tend to foster internal business efficiency through e.g. reduction of error rates, cycle, and waiting time, improved process transparency, and increased workflow and productivity.
