The effect of knowledge management practices on firm performance Daniel Palacios Marque´s and Fernando Jose´ Garrigo´s Simo´n
Abstract Purpose – This research proposes to study the connection between knowledge management practices and firm performance. Design/methodology/approach – Theoretical relations are tested through an empirical study carried out on 222 Spanish firms in the biotechnology and telecommunications industries.
Daniel Palacios Marque´s and Fernando Jose´ Garrigo´s Simo´n are both Associate Professors at the Department of Business Administration, Universitat Jaume I, Campus Riu Sec, Castello´n, Spain.
Findings – This paper shows how the firms that adopt knowledge management practices obtain better results than their competitors. Research limitations/implications – The subject of principles has not been considered a dimension of knowledge management. New avenues of inquiry are opened considering this dimension. Practical implications – It determines practices that have a positive incidence on firm performance. Originality/value – The conceptualization of knowledge management practices represents a theoretical innovation. This scale can be used in other knowledge-intensive industries. The paper concludes that these practices have a positive incidence on firm performance. Keywords Knowledge management, Organizational performance Paper type Research paper
Introduction In the last decade, knowledge management (KM) has become a line of research attracting much interest. Although the literature had already worked implicitly with knowledge, the increasing spread of theoretical works on KM is due to the importance it has for the firm, as well as the development of the competence-based view (CBV). The aim of this research is to study the importance of KM as a source of sustainable competitive advantages for firms and to analyze how the introduction of KM practices enables firm performance to improve. The practices that have a more positive influence on firm performance are also obtained. To achieve this aim, it is initially analyzed the theoretical framework of KM in order to specify the features and processes by which economic rents are created. Firstly, it is necessary to conceptualize KM as a starting point for designing an instrument for measuring it in the firm.
This research was supported by a grant (SEC2003-01825/ECO) from the Spanish Ministry of Science and Technology and FEDER (European Fund for Regional Development) and BANCAJA grant for visiting lecturers.
DOI 10.1108/13673270610670911
In order to develop the various objectives proposed in the paper, it is necessary to take account of different theoretical fields. CBV includes a set of approaches with a common factor, the importance of intangible assets as source of sustained competitive advantages. In this sense, this approach focuses on the importance of firms’ specific competences in their strategy and performance. Foss (1996, p. 1) emphasizes this approach and states that a firm can be conceptualized as a set of competences, and the ability of the firms to accumulate, protect and develop competences is the key to getting the competitive advantage.
VOL. 10 NO. 3 2006, pp. 143-156, Q Emerald Group Publishing Limited, ISSN 1367-3270
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‘‘ To estimate the benefit of a KM program, a conceptual perspective is required, as well as the use of tools and methods, rather than the ad hoc use of analytical approaches. ’’
Sanchez et al. (1996) accentuate the role of learning in organizations as an enabler for the process of creation of competences. In fact, for Sanchez et al. (1996, p. 3): CBV supposes that firms compete through learning based on experience, in order to develop competences that are used in different business activities and make possible the development of individual products.
However, there are some disadvantages which have slowed down the diffusion of the approach as a leading paradigm and its recognition as ‘‘business theory’’. In this sense, it has been reviewed as being essentially static and for laying emphasis on individual resources (Knudsen, 1996), so the approaches with a dynamic view are the ones that have made progress.
Conceptualization of KM Although in the last few years KM has become quite an important line of research, it is still difficult to find a conceptualization commonly accepted by anyone. The literature stresses the application of knowledge in the firm, through its human capital or in assets placed in the firm as patents, routines, databases, etc. to value creation. The definitions proposed by Lei et al. (1996) and Beckman (1997) fit the aims pursued in the research, as they relate KM to the creation of distinctive competences. However, most definitions consider KM as a set of phases, not taking into account the relationship with the distinctive competences. The KM conception used is not irrelevant. In this sense, KM includes new elements which determine the management method, although KM it is not considered as a new management paradigm, as it has neither a properly structured methodology nor a prescriptive framework for the successful management of any type of organization (Johannessen and Olsen, 2003). KM is considered a managerial system that captures established models of organization and broadens them to provide a practical methodology. KM practices refer to a more practical and perceptible level of research. From this dimension, KM can be viewed as an organizational innovation involving important changes in the introduction of the strategy and in traditional management practices. Works that have focused on the process of introduction of KM in the firm have centered on the most relevant areas so the system can be applied effectively. A review of the literature enables us to identify the following set of practices: B
orientation towards the development, transfer and protection of knowledge;
B
continuous learning in the organization;
B
an understanding of the organization as an overall system;
B
development of an innovative culture to encourage R&D projects;
B
approach based on individuals; and
B
competence development and management based on competences.
Dibella and Nevis (1998) admit that the overall conception of the organization as a successful factor in the introduction of the KM in the firm. KM can be understood from a
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global view drawing together not only the functions of an organization, but all its members, as well as all the organizations that have a direct relationship with it.
Literature review The study of the possible effects of introducing KM in the firm has centered on determining whether it is able to carry out quantifiable improvements. As Davenport (1999) points out, although the relationship between KM and performance indicators has been discussed at length (exchange value, market value, balance sheet, etc.), few firms have been able to establish a causal relationship between KM activities and firm performance. Firestone (2001) proposes an intuitive approach to clarify the relation between KM, corporate objectives and benefits. He suggests an abstract model called ‘‘benefit global estimation’’. To estimate the benefit of a KM program, a conceptual perspective is required, as well as the use of tools and methods, rather than the ad hoc use of analytical approaches. To relate KM programs and firm performance, the previous analysis of corporate objectives and business processes is required. In this sense, KM is a business process that can help firms reach their goals. Firestone (2001) argues that a KM program is made up of tasks (T1, T2, . . . , Tn). These tasks have an impact on business processes (P1, P2, . . . , Pn) and are compounded by different attributes which determine their present state. The difference between the present state and the objective state aids the understanding of how the introduction of a KM program influences firm performance. One of the main problems of this model is the excessive simplicity of the effects deriving from the introduction of KM in the firm. There are variables related to human capital that the model does not include, such as the improvement of its capabilities or skills. Davenport (1999) relates KM activities with some intermediate activities that affect financial results. Progress in KM activities affects intermediate variables such as project performance measurements, indicators of the capacity of employees to carry out tasks related to knowledge, and finally, the generation of ideas and innovations. The generation of new ideas and innovations in the firm, due to a better use of knowledge, could have an effect on the improvement of processes. In the same way, an improvement in processes perfects employees’ capabilities. Wiig (1999) creates a cause and effect diagram depicting the effects of introducing a KM program. The added value of the model lies in introducing all the effects deriving from a program that encourages the creation and sharing of knowledge. Decarolis and Deeds (1999) study the impact of organizational knowledge on firm performance. Organizational knowledge is conceptualized through stocks and flows of knowledge (Dierickx and Cool, 1989). Knowledge stocks accumulate knowledge assets that are internal to the firm. Flows refer to all the elements able to modify the stock of knowledge. A suitable context for examining stocks and flows of organizational knowledge and its relationship with firm performance is a dynamic industry in terms of knowledge generation, so the authors are using the biotechnology sector for the empirical study. Decarolis and Deeds (1999) conclude that from the variables used to make flows of organizational knowledge operational, only the munificence of the geographical area is significant. This means geographical location influences capacity for capturing knowledge. As for the variables used to measure knowledge stocks, there are two that positively affect firm performance: the number of products that the firm is developing and the number of
‘‘ There are no models that measure the relationship between KM practice and firm performance. ’’
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times works created by a firm are cited. In addition, organizational knowledge stocks have greater impact on firm performance than knowledge flows. However, there are no models that measure the relationship between KM practices and firm performance. The theoretical model proposed is shown in Figure 1. Now, from the theoretical model, the main hypotheses of the research are developed. H1.
The degree to which an organization takes on the introduction of KM practices is positively related to firm performance.
The acceptance of these practices or techniques creates an appropriate environment for the development of some distinctive competences (Lei et al., 1996; Beckman, 1997). This hypothesis can be formulated by distinguishing every dimension of the KM practices. H1a. There is a positive relationship between the orientation towards the development, transfer and protection of knowledge and firm performance. H1b. There is a positive relationship between continuous learning in the organization and firm performance. H1c. There is a positive relationship between an understanding of the organization as a global system and firm performance. H1d. There is a positive relationship between the development of an innovative culture that encourages R&D projects and firm performance. H1e. There is a positive relationship between an approach based on individuals and firm performance. H1f. There is a positive relationship between competence development and management based on competences and firm performance.
Figure 1 Theoretical model
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Dibella and Nevis (1998) state that the introduction of KM programs facilitates the acquisition of new knowledge, which will have a bearing on the creation of new routines and mental models. Ranft and Lord (2002, p. 420) hold that knowledge transfer occurs when knowledge-based assets are acquired and used. So, an organization directed towards knowledge development and transfer allows its human capital fast and unimpeded access the knowledge (Szulanski, 1996). Besides, the importance of knowledge as basic factor to create competitive advantages is reinforced in industries that are constantly innovating (Decarolis and Deeds, 1999).
Research methodology The biotechnology and telecommunications industries have been chosen for the research because the management of intangibles is appreciated more clearly than in other types of industries. Knowledge is not a simple asset but it focuses other assets. To be successful, firms must be able to learn continually and apply their knowledge, anticipating market changes (Alvesson, 2000). In this environment, the ability to create and apply knowledge becomes an important source of competitive advantages. In the biotechnology industry, the development cycle is long if it is compared with other industries, but nowadays it is emphasizing the speeding up of the rhythm of scientific discoveries in order to reach the market first, and the reduction and control of expenditure on R&D at all the levels. In 2001, according to the Spanish National Statistical Institute, the number of Spanish firms belonging to the biotechnology industry was 226, while in the telecommunications industry there were 846. The Spanish National Statistical Institute includes a database with information about biotechnology and telecommunications industries: address, telephone and fax numbers, e-mail, business activities and directors’ full names. The questionnaire respondent was the manager of the firm, as this person has the overall information about the organization necessary for answering the questions. A total of 257 questionnaire responses were achieved. The statistical debugging of the questionnaires meant 35 of them had to be eliminated for various reasons (existence of items without answers, doubts about the reliability of the responses, etc.). The sample finally included 222 firms (102 from the biotechnology industry and 120 from the telecommunications industry) so the response rate was 45.1 and 14.2 percent respectively. This final sample has a statistical margin of error of ^ 5.7 percent, with a 95.5 percent confidence interval. As for the general features of the respondents, the average number of employees was 123, the annual turnover was e30,160,000 and the annual R&D budget was e3,860,000. The technical specification can be found in Table I. The questionnaire is made up of two parts, corresponding to the two theoretical constructs postulated in Figure 1. The first one measures KM practices. The scale was made up of 23 items (see Appendix 1). To measure KM practices a Likert scale from 1 to 7 was used. The respondent answers 7 if the practice is always used with an established method in the organization, 1 if the practice is never used and an intermediate number if the practice is used sporadically.
Table I Technical specifications of the empirical work Sample Scope Sample size Margin of statistical error Fieldwork period
Biotechnology and telecommunication firms Spanish firms (questionnaire carried out by mail) 222 firms ^5.7 percent (95 percent significance level) December 2001-March 2002
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‘‘ One of the problems in the area of KM is the inability to measure the most important concepts. ’’
In this research it is used the scale designed and validated by Camiso´n (2004). It includes a dimension for the capacity to compete, outstanding in strategy theory, especially in the research carried out (Appendix 2). The generic procedure used to develop the two measurement scales (KM and firm performance) is based on Churchill (1979) and DeVellis (1991). Measurement scales are obtained using a Delphi study consulting KM experts from academic and business backgrounds, a pre-test, and a validation process based on confirmatory factorial analysis. All sociometric properties (dimensionality, reliability and validity) required for measurement scales in social sciences have been checked for the two scales. The panel of experts was made up of 22 people with the following backgrounds: two recognized experts from each industry included in the empirical study plus eight academics of international origin. The 12 industrial experts were company managers and specialists in the industry coming from business associations or institutions related to the sector. Academics were experts on knowledge management. This plurality in the panel of experts prevents bias in the information. By allowing group members to consider their answers and reply in private, undue social pressures are avoided. No member of the panel can be influenced by the others, the only influence is the coherence of the argument. The identification of the attributes to form part of the measurement instrument has followed the recommendations in the literature, being carried out in two stages. The first stage consists of bringing together a broad sample of items including the greatest possible number of attributes configuring all the dimensions of the construct domain. The technique used to generate items has been an extensive review of the literature relating to the construct. Next, it is necessary to reduce the number of items so the measurement instrument may be applied for empirical research, selecting only relevant attributes that are real determinants for evaluation. To reduce the scale it has been resorted to the Delphi technique and, then, to carrying out a pre-test. Respondents indicated the extent of their agreement on a seven-point Likert scale. The mean of the median for the items was 6.1. As it was very high, the process for eliminating items was difficult, following these criteria: B
eliminate items where the mean of the median was lower than 5.6;
B
draw up or eliminate items with greater variability in the answers. These items do not reach a high degree of consensus between the experts; and
B
include the experts’ suggestions. According to them, items considered similar can be grouped.
After carrying out two rounds, the items with the lowest level of agreement were removed and the suggestions for improving the measurement scales received from the experts were included, with the consultation of experts considered as completed. The analysis of the results obtained indicates that the majority of the items are important in determining the scope of the construct to be measured, enjoying a high degree of consensus from the expert panel. EQS 5.7 was used to test the theoretical model postulated in Figure 1. Through its flexible interplay between theory and data, the structural equation model approach bridges theoretical and empirical knowledge for a better understanding of the real world (Fornell and Larcker, 1981). Such analysis allows for modeling based on both latent (unobservable) variables and manifest (observable) variables, a property well suited for the hypothesized
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model, where most of the constructs represented are abstractions of unobservable phenomena. Furthermore, structural equation modeling takes into account errors in measurement, variables with multiple indicators, and multiple-group comparisons.
Results Before developing the causal relationship proposed in the hypothesis, it is necessary to verify that the measurement scales are useful for gathering information on the construct to be evaluated, and furthermore that this information is obtained by the most accurate and true-to-life procedure possible. A useful, faithful and accurate instrument for measurement must meet three requirements: 1. Dimensionality. 2. Reliability. 3. Validity. Dimensionality The aim of the dimensionality analysis consists of verifying the existence of the dimensions proposed in the theoretical model. KM practices scale. The study assumes KM practices to be a second-order measurement model, comprising six dimensions. The fit indices for this model are shown in Table II. The fit indices are statistically significant, so it is assumed that the model developed to measure KM practices is dimensionally correct. Another important question is determining the weight of the six dimensions (Table III). The approach based on individuals (0.912) and management based on competences (0.872) are the two dimensions with the greatest weight in the KM construct. This highlights the relevance of the human dimension, necessary for developing an effective KM strategy. From the results, it can be deduced that this is more important than the development of an Table II Fit indices for KM practices Chi 2 Satorra-Bentler df Orientation towards the development, transfer and protection of knowledge Continuous learning in the organization An understanding of the organization as a global system Development of an innovative culture that encourages R&D projects Approach based on individuals Competence development and management based on competences
P
BB NFI
IFI
GFI
AGFI
PGFI
0.0289 0.0811
2 1
0.8595 0.2956
0.9972 0.9452
0.999 0.9587
0.9952 0.9586
0.9762 0.9198
0.9856 0.9365
0.856
2
0.6523
0.9740
0.9795
0.9625
0.9478
0.9785
0.965 0.0365
2 2
0.5263 0.8462
0.9553 0.9947
0.9584 0.9976
0.9377 0.9917
0.9101 0.9744
0.9562 0.9832
0.0726
1
0.3125
0.9402
0.9458
0.9256
0.9103
0.9289
Notes: BB-NFI ¼ Bentler-Bonett normed fit index $0.9; IFI ¼ Incremental fit index (good values around 1); GFI ¼ LISREL goodness of fit index $0.9; AGFI ¼ LISREL adjusted goodness of fit index $0.9; PGFI ¼ Parsimony adjusted fit index $0.9
Table III Loadings for KM practices Measurement
Loading
Orientation towards the development, transfer and protection of knowledge Continuous learning in the organization An understanding of the organization as a global system Development of an innovative culture that encourages R&D projects Approach based on individuals Competence development and management based on competences
j
0.672 0.841 0.582 0.728 0.912 0.872
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innovative culture encouraging R&D projects, which it is capital in the biotechnology and telecommunications industries. Firm performance scale. The study assumes firm performance to be a second-order measurement model, comprising five dimensions (capital profitability, growth, operational and financial efficiency, stakeholder satisfaction and competitive position). The fit indices for this model are shown in Table IV. All of them are statistically significant. Reliability Measurement of internal consistency and stability of the scales. Determining reliability is equivalent to establishing the quality of the instruments used, in the sense that the structure of the scales is correctly designed, and the measurements are therefore free from the distortions produced by casual errors. The process of refinement by the Delphi method and the pre-test will have minimized this effect. In the study, it is calibrated the reliability of the scales using two methods, the compound reliability coefficient and the re-test method, each of which evaluates one of the two dimensions of reliability: consistency and stability. The re-test procedure. The re-test was sent to the first 200 respondents to the survey. The time between the two measurements was approximately 45 days, a period considered long enough to prevent the first measurement influencing the second, but short enough for the context not to have changed. Following the first mailing procedure, the respondents were sent a reminder card after two weeks. A total of 172 firms finally participated in this re-test exercise, but three had to be rejected due to defects of form or inconsistencies in content, leaving the final rate of response to the re-test at 84.5 percent. The scale built is stable, since there were no significant differences between the content of the answers in the two mailings. The compound reliability coefficient. The statistic used for determining the reliability of the measurement based on its internal consistency is the compound reliability coefficient. This coefficient is greater than 0.7 in all the dimensions, which is the acceptable minimum. As a result, it can be concluded that KM dimensions are accurately measured. This means that the items chosen to measure each dimension are reliable. Validity of the scales The validity of a measurement refers to the degree to which the measuring process is free from both systematic and random error. In contrast to the case of reliability, no statistic offers a general index of validity of the measurements made. There are three basic types of validity. Content validity. Content validity indicates that the procedure for developing the measuring instrument is adequate (Nunnally, 1978). The content validity of a scale is difficult to verify, because there is no objective criterion for its evaluation. One frequently used procedure is to verify whether the process of construction of the scale fits the criteria suggested in the literature, both in methodology and the techniques and coefficients used. With regard to methodology, this study was carried out in accordance with the recommendations made by (Churchill, 1979). This methodology, with adaptations, has been used by a wide-range of authors to construct scales for measuring key constructs in strategy. With regard to techniques or coefficients, scales were developed with the instruments normally used in this type of study, such as the literature review or compound reliability coefficients. When elements other than those listed by Churchill (1979) were introduced, they were in all cases adapted from earlier studies on measurement scales, as with the Delphi methodology for Table IV Fit indices for firm performance Chi 2 Satorra-Bentler
df
p
BB NFI
IFI
GFI
AGFI
PGFI
0.0663 0.0811 0.0556 0.0693 0.0597
2 1 2 2 2
0.5126 0.2956 0.7352 0.5121 0.5365
0.9522 0.94 0.9901 0.95 0.98
0.9621 0.94 0.9935 0.95 0.98
0.9786 0.94 0.9878 0.95 0.98
0.9532 0.9198 0.9656 0.9371 0.9601
0.9485 0.9365 0.9877 0.9512 0.9742
Capital profitability Growth Operational and financial efficiency Stakeholder satisfaction Competitive position
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reducing the scale (Malhotra, 1981) or the re-test method for evaluating the reliability of the scale (Conant et al., 1990). Convergent validity. Convergent validity is said to exist when the measurement is strongly and positively correlated with other measurements of the same construct (Churchill, 1979), or with the variable with which it should theoretically correlate. As Bentler-Bonett coefficient is greater than 0.9, the magnitude of factorial loadings is . 0:4 and all the parameters estimated are statistically significant at 95 percent (t $ 1:96), convergent validity is proved. This property provides evidence that the items all converge on the same construct Discriminant validity. This indicates to what extent two measurements developed for similar but conceptually different constructs are related (Bearden et al., 1993). In Table V, for all the dimensions, 15 chi-squared tests were carried out, in which the difference between the values of two chi-square models is gathered, one in which a perfect correlation is considered and a second one in which there is no correlation. Chi-square values have statistically significant differences (p # 0:05), so every dimension represents a different concept, and the existence of discriminant validity is therefore proven. So, it is demonstrated that the two scales (KM practices and firm performance) meet the sociometric requirements required for scales in social sciences. Now the causal relationships formulated in the hypothesis are studied.
Causal relationships The estimated parameters and reliability index for the first hypothesis structural model is shown in Table VI. All the structural models fit properly, so the first hypothesis and the six sub-hypothesis that can be derived from it have been verified. It is important to highlight that the reliability parameter used is not very high in all the models. This is due to the fact that there are other variables that affect firm performance that are not included in the model. From the results it could be concluded there is a strong and positive relationship between the adoption of KM practices and firm performance. Table V Chi-square tests to analyze discriminant validity
T1 T2 T3 T4 T5 T6
T1
T2
T3
T4
T5
0.526 0.325 0.526 0.251 0.423
0.425 0.356 0.353 0.463
0.542 0.487 0.125
0.329 0.219
0.65
T6
Note: T ¼ technique
Table VI Estimated parameter and reliability index Model KMP ! FP (H1) KM P1 ! FP (H1a) KM P2 ! FP (H1b) KM P3 ! FP (H1c) KM P4 ! FP (H1d) KM P5 ! FP (H1e) KM P6 ! FP (H1f)
g coefficient in the equation FP ¼ gKMP þ D
Structural equation reliability (R 2)
0.921 0.715 0.763 0.708 0.801 0.845 0.802
0.582 0.449 0.458 0.442 0.477 0.498 0.489
Note: *All the estimated parameters are significant at a 95 percent confidence level (t $ 1:96)
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Conclusions and managerial implications When KM practices were conceptualized, the existence of a factorial structure distinguishing six dimensions was assumed. The introduction of the six dimensions makes it easier for managers to focus their attention on them, determining the specific actions to carry out to introduce them. Results highlight the relevance of the human dimension, necessary for developing an effective KM strategy. One of the problems in the area of KM is the inability to measure the most important concepts (Decarolis and Deeds, 1999; Davenport, 1999). Through this study, it is obtained an instrument for measuring the key element of this topic, the degree to which KM practices have been introduced in the firm. As for the generalizability of the scale, it can be used in other knowledge-intensive industries such as software or consultancy, as there are no items specific to the industries included in the empirical study. In addition, the methodology developed here may also serve as a reference in the process of conceptualization, operationalization and measurement of all the other basic constructs in strategic management, all of a clearly multidimensional nature, due to the number of dimensions or elements that play a part in their definition. The problems underlying the empirical study of such variables and of their inter-relationships, deriving from the difficulty of measurement, also find some useful working proposals in the study. The instrument developed adopted a qualitative scale of classification, which allows managers’ experience and opinion to be translated into subjective measurements of intangible assets. Another important result of the research is the validity of the procedure for measuring using a subjective scale, constructed on the basis of managers’ self-classification of the firm in relation to their competitors. The reliability and the validity of measuring by this means leads us to consider it as a replacement for objective measures based on proxy variables, whose representation of the attributes of the construct tend to lack completeness. As refers to the generalizability of the scale, it can be used in other knowledge-intensive industries such as software or consultancy, since there are no items specific to the industries analyzed in the empirical study. In the same way, the findings of Spain-based organizations are equally applicable to organizations in the same sectors located in other countries, regions, since there are no items specific to Spain-based organizations. With the development of this instrument, new avenues of inquiry are opened. Intermediate variables could be introduced, as Davenport (1999) states. In addition, and following Decarolis and Deeds (1999), a longitudinal study could be developed to determine how and when firm performance changes with the introduction of KM. Another level of analysis could be considered, taking into account stocks and flows of knowledge.
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Appendix 1 Table AI Scale for measuring KM practices Items
Average
Orientation towards the development, transfer and protection of knowledge R1 The firm has a system to codify its explicit knowledge 5.618 R2 Information technologies and systems (intranet, internet, etc.) are available to give the employee access to the information required 4.875 R3 Mechanisms are in place to encourage the members of an organization to share information 4.209 R4 Inter-departmental projects are carried out in the firm 6.436 Continuous learning in the organization R5 The firm has a career plan to stimulate continuous learning R6 Employees receive general training which is applied to their usual tasks R7 A continuous improvement system is in place allowing for improvement in processes which have reached the set quality standards An understanding of the organization as a global system R8 A system exists to inform clients, suppliers, employees, according to the needs detected R9 The firm encourages knowledge transfer through instruments such as inter-functional teams, quality circles, improvement groups, etc. R10 Best practices in one department are shared by others R11 There are incentives when the overall aims of the firm are achieved R12 The firm has systems that capture and deal with information about processes Development of an innovative culture that encourages R&D projects R13 Employees who develop R&D projects have the necessary training to put them into practice R14 Techniques are established to develop external benchmarking, which enables the company to learn about the success or failure of other firms R15 R&D projects are provided with control mechanisms to monitor them R16 When an R&D project finishes, feedback is obtained that is useful in developing new projects Approach based on individuals R17 Tasks are established to identify the information resources necessary for the organization R18 The firm encourages teamwork R19 Procedures are established (such as surveys or discussions) to find out employees’ opinions and levels of satisfaction R20 The managers inform of and reward their collaborators’ achievements
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1.056
0.985 1.259 0.812
5.623
1.063
6.203
0.956
5.962
0.463
6.378
0.914
5.711 6.325
1.662 1.105
5.669
0.712
6.399
0.603
4.250
1.289
3.127
1.841
6.873
0.772
6.669
1.154
3.952 5.691
1.548 1.236
3.125
0.852
3.695
1.962
Competence development and management based on competences R21 The organization has systems to measure its employees’ competences 3.712 R22 Remuneration and promotion systems have an influence on the development of competences, ideas and knowledge by the employees 4.185 R23 The firm uses benchmarking techniques to improve its employees’ competences 5.266
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Standard deviation
0.996
1.255 0.744
Appendix 2 Table AII Scale for measuring organizational performance Items
Average Standard deviation
Capital profitability R1 Average economic profitability ROA (subjective scale 1-5) Average economic profitability ROA (book value in percent) R2 Average financial profitability ROI (subjective scale 1-5) Average financial profitability ROI (book value in percent) R3 Average profitability in sales ROS (subjective scale 1-5) Average profitability in sales ROS (book value in percent) R4 Average gross production margin (subjective scale 1-5) Average gross production margin (book value in percent) Growth R5 Average annual growth in sales 1997-2001 (subjective scale 1-5) Average annual growth in sales 1997-2001 (book value in percent) R6 International annual average growth in sales 1997-2001 (subjective scale 1-5) International annual average growth in sales 1997-2001 (book value in percent) R7 Market share increase 1997-2001 (subjective scale 1-5) Market share increase 1997-2001 (objective value in percent) R8 Expected growth in sales 2002-2004 (subjective scale 1-5) R9 International expected growth in sales 2003-2005 (subjective scale 1-5) Operational and financial efficiency R10 Financial solvency (subjective scale 1-5) Financial solvency – ratio total debt/own assets (book value) R11 Financial liquidity (subjective scale 1-5) Financial liquidity – ratio current assets/current liabilities – (book value) R12 Labor productivity (subjective scale 1-5) Labor productivity – ratio added value/average total personnel (objective value in millions e) R13 Cost-efficiency – total unit cost of the product – (subjective scale 1-5)
3.512 7.493 3.412 6.017 3.386 5.920 3.127 33.115
0.793 16.321 1.221 7.433 0.993 4.992 1.025 25.479
3.234
1.160
10.318
3.124
3.369
0.782
6.815 3.577 4.199 3.440
2.193 0.857 1.442 0.816
3.204
1.205
3.593 1.723 3.104
0.791 0.661 1.441
1.123 3.265
0.336 0.843
3.104
1.698
3.580
1.001
Stakeholder satisfaction R14 Wealth creation (subjective scale 1-5) Wealth creation – ratio market value/book value (objective value) R15 Customer satisfaction (subjective scale 1-5) R16 Employee satisfaction (subjective scale 1-5) R17 Global image of the environment (subjective scale 1-5)
3.183
1.376
1.672 3.347 3.312 3.206
0.502 0.925 0.651 1.389
Competitive position R18 Domestic competitive position (subjective scale 1-5) R19 European competitive position (subjective scale 1-5) R20 Overall competitive position (subjective scale 1-5) R21 Prices/internal competitive position (subjective scale 1-5) R22 Prices/external competitive position (subjective scale 1-5) R23 Quality/internal competitive position (subjective scale 1-5) R24 Quality/external competitive position (subjective scale 1-5)
2.914 3.813 2.777 3.124 3.118 2.192 2.443
1.733 1.393 1.350 0.813 0.946 1.533 1.619
2.911 3.218
1.568 1.590
Firm’s competitive position* Firm’s overall performance**
Notes: *Calculated as average of items of the dimension ‘‘competitive position’’ (R18 to R24); **Calculated as average of 24 scale items; Cronbach alpha coefficient of firm overall performance scale ¼ 0:9037; Cronbach alpha coefficient of firm competitive position scale ¼ 0:8134
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About the authors Daniel Palacios Marque´s PhD is an Associate Professor in the Department of Management, Universitat Jaume I (Spain). Engineer in Computer Science from the Polytechnic University of Valencia (Spain). Master’s Degree in Information Systems, Polytechnic University of Valencia (Spain). Visiting Scholar at the International Centre for Information Technologies in Pisa (Italy) and the Department of Business in Saldford University (England). He has carried out several research projects supported by the Spanish government related to the introduction of knowledge management in the firm. He has also developed an intranet for knowledge management with consultant and software firms. Daniel Palacios Marque´s is the corresponding author and can be contacted at:
[email protected] Fernando Jose´ Garrigo´s-Simo´n PhD is an Associate Professor in the Department of Management, University Jaume I (Spain). Degree in Economic and Entrepreneurial Sciences, University of Valencia (Spain). MSc in Tourism Management and Planning, Bournemouth University (England). Visiting Scholar at the International Centre for Tourism and Hospitality Research (Bournemouth University), Visiting Fellow at Institute of Management Science, Walailak University (Thailand) and Visiting Fellow at the Miami University.
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