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Int. J. Knowledge and Learning, Vol. 2, Nos. 1/2, 2006
Knowledge-based strategies and information system technologies: preliminary findings Meir Russ* Department of Business Administration University of Wisconsin-Green Bay Wood Hall 460 G, 2420 Nicolet Drive Green Bay, WI 54311–7001, USA Fax: 1–920–465–2660 E-mail:
[email protected] *Corresponding author
Jeannette K. Jones Franklin University 201 S. Grant Avenue Columbus, OH 43215, USA Fax: 1–614–224–3742 E-mail:
[email protected] Abstract: Knowledge-Based (KB) strategies are being recognised as a vital factor of business strategy. Still, there is limited empirical research in this young academic field. This research intends to add to the limited empirical research in the area of Knowledge Management (KM) and Information Systems (IS) technologies. This research uses a recently proposed framework to analyse the relationship between six KB strategic dimensions, organisational culture, and IS technologies. The results indicated that two KB strategies had a positive association with a number of IS technologies, but not all types of IS technologies. Further, only one IS technology showed statistically significant association with one of the outcomes tested. Keywords: knowledge-based organisational culture.
strategy;
taxonomy;
IS
technologies;
Reference to this paper should be made as follows: Russ, M. and Jones, J.K. (2006) ‘Knowledge-based strategies and information system technologies: preliminary findings’, Int. J. Knowledge and Learning, Vol. 2, Nos. 1/2, pp.154–179. Biographical notes: Dr. Meir Russ received his MA and PhD from The Ohio State University, USA and his BScEE and MBA from Tel Aviv University, Israel. He is currently an Assistant Professor at UW-Green Bay, where he teaches Innovation, Strategy, Management and Marketing classes in the Graduate and Undergraduate Programme of Business Administration. His research interest includes Knowledge Management strategies and technologies as well as Viral Marketing.
Copyright © 2006 Inderscience Enterprises Ltd.
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Dr. Jeannette K. Jones received her BS in Human Resource Management from George Mason University in Fairfax, Virginia, her MBA from Averett College in Danville, Virginia, and her EdD in Instructional Technology and Distance Education from Nova Southeastern University in Ft. Lauderdale, Florida. She is currently a Lead Design Faculty member at Franklin University where she is responsible for the curriculum design of Graduate and Undergraduate programmes and online Faculty Development instruction. Her research interests include knowledge management strategies and technologies, Online Learning theory and design, and Coaching methodologies. An earlier version of this paper was presented at the IEMC 2005 Conference, St. John’s Newfoundland, Canada; 11–14 September 2005.
1
Introduction
As the new-knowledge economy continues to move forward, knowledge is being considered a crucial component of business strategy (e.g., Teece, 2000b). Consequently, the capacity to manage knowledge is becoming an essential skill for acquiring and sustaining success and organisational survival in the new-knowledge economy (Grant, 1996). Recently, the topics of knowledge and Knowledge Management (KM) detonated an increase of interest in both academic and popular literature (e.g., Kluge et al., 2001; Ruggles, 1998). Notwithstanding this ‘hype’, and in particular after the ‘burst of the internet bubble’, the need for an enhanced command of managing knowledge and knowledge management is keener than ever (e.g., Davenport and Grover, 2001; Gilmour, 2003; Soo et al., 2002). This research adds to the limited empirical data in the area of KM and Knowledge-Based (KB) strategies (Bierly and Chakrabarti, 1996), Information Systems (IS) technologies (Khandelwal and Gottschalk, 2003), culture, and performance (Hoopes and Postrel, 1999). It is exceedingly imperative that additional empirical research be presented for validation if, indeed, developing, acquiring, and managing knowledge assets is central for a company’s success. This research is the continuation and an addition to an early paper (Russ et al., 2006) that introduced the C3EEP framework of KB strategies. The results of that study (Russ et al., 2006) demonstrated that the KB strategies had a direct and indirect association with organisational outcomes and culture. Earlier research also identified the significant relationship that two (out of the six) KB strategies have with some of the IS technologies studied (Russ et al., 2004; Russ et al., 2005). This article will assess the relationship that the C3EEP KB strategies have with IS technologies, incorporating further research data and analysis. The paper starts with the description of the six validated KB strategic dimensions. The descriptions will be followed by a brief discussion about KM and culture relationships. In addition, the relevance of IS for KM strategies will be discussed. Based on these discussions, a number of hypotheses will be offered followed by the research method, the findings, and conclusions. The paper will conclude with a discussion of the limitations of the research.
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2
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Knowledge-Based (KB) strategies
Given the strategic KB dilemmas that companies are struggling with, are specific IS technologies better than others? This is the basic question that this research is discussing. The strategic KB choices that companies make can be either deliberate (comprising strategic intent) or emerging (Mintzberg and Waters, 1985), implicit or explicit (e.g., Bierly and Chakrabarti, 1996). Based on the literature review and previous research, the C3EEP framework of strategic dilemmas was used. 1
Codification-Tacitness
2
Complementary-Destroying
3
Concealment-Transparent
4
External Acquisition-Internal Development
5
Exploration-Exploitation
6
Product-Process.
The following will elaborate on each choice dilemma: •
Ought the company focus on codifying the knowledge or would it be better off leaving the knowledge tacit (e.g., Conner and Prahalad, 1996; Hansen et al., 1999; Leonard-Barton, 1995; Schultz and Jobe, 2001; Spender, 1996; Subramaniam and Venkatraman, 2001)? This research puts forward (similar to Schulz and Jobe, 2001) that tacit-explicit knowledge is a choice opportunity that companies have made either implicitly or explicitly. The research also assumes that the choices made are continuous and not dichotomous (e.g., Holden, 2001; Kluge et al., 2001; Russ et al., 2006). It is understood that it is the company’s decision (and strategy) how to balance and where on the continuum the company want to position itself.
•
Ought the company focus on developing knowledge that is complementary to its current KB or would it be better off developing new knowledge even if this destroys the existing KB (e.g., Barley, 1986; Bower and Christensen, 1995; Fleming, 2001; Hill and Rothaermel, 2003)? In this research, the complementary strategy is described as a strategy based on using and developing only knowledge that is congruent to the currently obtainable knowledge base within an organisation (e.g., Hill and Rothaermel, 2003). Such knowledge could potentially be even ‘new to the world’ innovation, but will be supportive and related to the existing knowledge base of the company (e.g., Hargadon, 1998). On the other hand, the destroying strategy can be described as a strategy focused on mounting a new-to-the-company knowledge base while destroying the current knowledge base in order to develop a unique competitive advantage allowing the company to revolutionise the industry (e.g., Hill and Rothaermel, 2003; Kim and Mauborgne, 2005). This research postulates that more and more companies are aware of the risks they might be taking by avoiding/underestimating breakthrough innovations. A rising number of established companies are, therefore, engaged in incorporating (at least some) aspects of destroying strategies (see for example Casillas et al., 2000; DeTienne and Koberg, 2002; Stringer, 2000; Kim and Mauborgne, 1999).
Knowledge-based strategies and information system technologies •
157
Ought the knowledge be transparent or would the company be better off keeping the knowledge concealed (e.g., Gray, 1988; Inkpen, 1998; Lamming et al., 2001; Radebaugh and Gray, 1997; von Furstenberg, 2001)? For example, in the area of strategic alliances, where learning and knowledge have been identified as a critical issue (e.g., Hamel, 1991), Inkpen (1998) identifies the matter of how shielding the partners of their knowledge is used as a decisive aspect of the knowledge acquisition process between partners. Appleyard (1996) developed a framework for knowledge sharing among firms within an industry. She identifies three rationales for why companies may want to share knowledge with competitors: a
formation of industry standards
b
receiving inputs into their planning
c
getting acceptance into professional networks.
Appleyard (1998) also insinuates that it is up to the companies to instruct their employees about what and how knowledge can be shared. Tapscott and Ticoll (2003) carry this argument one step further, suggesting that companies should see transparency as an opportunity (not as a threat) to build trusting relationships with both external and internal constituencies. •
Ought the company focus on getting the most from its existing knowledge or would the company be better off experimenting with new knowledge (e.g., Bloodgood and Salisbury, 2001; Fjeldstad and Haanaes, 2001; Levinthal and March, 1993; March, 1991; McGrath, 2001; Pitt and Clarke, 1999)? The focal point of the learning mechanisms varies: the exploration learning is variance-seeking while the exploitation learning is mean-seeking (McGrath, 2001), or what Bloodgood and Salisbury (2001) call reconfiguration of new resources versus reconfiguration of existing resources. The IS, culture, and reward systems that will be most effective for the two strategies might be incongruous (e.g., Pitt and Clarke, 1999). For example, IS can be very efficient for sharing existing knowledge that is important for exploitation strategy, but can be fairly ineffective in promoting the innovation and creativity that are important for exploration strategy. Balancing the two is seen as imperative in developing dynamic capabilities (e.g., Dickson et al., 2001; March, 1991), new service development (e.g., Menor et al., 2002), organisational adaptation (e.g., Tushman and Romanelli, 1985), research and development (e.g., McNamara and Baden-Fuller, 1999), and innovation implementation in high technology manufacturing (e.g., Jayanthi and Sinha, 1998), among many others.
•
Ought the knowledge be developed internally, or would the company be better off acquiring the knowledge from external sources (e.g., Appleyard, 1998; Bierly and Chakrabarti, 1996; Jones, 2000; Parikh, 2001; Pitt and Clarke, 1999; Steensma, 1996; Zack, 1999)? For example, development of new technologies for a new product or new processes can be either acquired from outside the firm through inter-organisational arrangements or those technologies can be develop internally (e.g., Appleyard, 1998; Pitt and Clarke, 1999; Steensma, 1996; Zack, 1999). Quinn (1999) identified a number of issues that companies need to be concerned with when considering strategic outsourcing. For example, completely losing skill sets, opportunistic risks, difficulty in precisely identifying expected outcomes, etc. This may suggest why companies might want to balance their dependencies on external
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M. Russ and J.K. Jones sources with their internal development. On the other hand, Teece (2000b) suggested that the mechanisms for transferring knowledge externally are very different from transferring knowledge internally within the company.
•
Ought the company focus on the KB that is supporting the process and creating the value, or should the focus of value creation and the KB supporting this be the product/service (e.g., Abernathy, 1978; Jones, 2002; Smith and Reinertsen, 1998)? For example, Jones (2002) suggested that companies loosing their radical innovative capabilities are starting to focus on value creation through process efficiencies, or they are acquiring innovative solutions from small innovative companies. In other words, a new solution that creates value can be either a cheaper product or a better new product (e.g., Smith and Reinertsen, 1998, p.23). A different type of choice dilemma is illustrated by Sanchez and Mahoney (1996) who claim that a choice of a product design is coupled with a choice of a process in a reciprocal relationship. For example, a tightly designed product will require a process that is intensively coordinated. These processes illustrate the companies’ realisation that the ‘what’ they produce might be as important as, the ‘how’, (see for example Martin’s, 1995, p.313, study of Wal-Mart).
Earlier research (for more details see below and also Russ et al., 2006) suggested that the above-mentioned choices are independent, meaning, a company can decide on each one of the six choices, as they are (at least potentially) not related.
2.1 KM and culture There is expanded academic literature linking culture and KM (e.g., De Long and Fahey, 2000; Gupta and Govindarajan, 2000; Inkpen, 1998; Lam, 1997). De Long and Fahey (2000) suggest that any discourse about KM that leaves out culture might be deficient. Holden (2001) takes this perspective one step further by postulating that culture is the habitat of knowledge and should be seen as an object of KM. Despite the extensive discussion in the academic literature linking KM and culture, there is very little empirical research about the association between culture and KM strategy or specific KB strategies (see Jassawalla and Sashittal, 2002; Moffett et al., 2002 for rare examples). This research paper will concentrate on two characteristics of culture: values and artifacts. The two are different but related features of organisational culture. The values that are commonly suggested by the KM literature as crucial for successful KM implementation, namely: trust, accessibility, and relationships (e.g., Martin, 2000); as well as the artifacts which represent the culture that is supportive of knowledge/data flow, specifically the office design, were included in the research (for additional in depth discussion, readers can see Russ et al., 2004; Russ et al., 2006). Earlier research (Russ et al., 2004; Russ et al., 2006) found significant relationships between culture, KB strategies, and outcomes. This research will expect similar results and will use culture as a control variable, since the focus of this study is on KB strategies and IS technologies.
2.2 KB strategies and outcomes This research will continue to look into two different outcome indicators – the ‘Process’ and the ‘Product’ outcomes. Earlier research (Russ et al., 2004; Russ et al., 2006) suggested that only Codification strategy is positively associated with the ‘Process’
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159
outcome. No other KB strategies had significant association with the ‘Process’ outcome. A possible explanation for this might be that for processes to be successful, codification will make it easier to manage and to control them (e.g., Davenport, 1993). The research also found that the exploration strategy has a positive and significant association with the ‘Product’ effectiveness (Russ et al., 2004; Russ et al., 2006). This finding is consistent with extensive literature discussing the importance of innovation and new product development for sustaining competitive advantage (e.g., Cooper, 2001; Teece, 2000a; Tushman et al., 1997). The major conclusion from the earlier research had been that companies that want to focus on Product effectiveness would be better served by having an Exploration external strategy as well as Codification strategy. The companies might also be better served having the knowledge developed internally, while companies that want to focus on Process improvement might be better served by having a proactive codification strategy and a KM supportive culture.
2.3 IS and KB strategy In pursuit of the competitive advantage within the new-knowledge based economy, companies invested heavily in IS (e.g., Ofek and Sarvary, 2001). The academic and popular literature suggests that for most (medium and large) firms, it is not practical to have a knowledge strategy or KM initiatives without having IS technologies in place (e.g., Hansen et al., 1999; Skyrme and Amidon, 1997; Tiwana, 2000). The literature also suggests that some IS technologies might be more appropriate in different contexts (e.g., Bloodgood and Salisbury, 2001), which is also supported by previous research (Russ et al., 2004; Russ et al., 2006). For example, Bolisani and Scarso (2000) suggest that some IS technologies might be better at facilitating communication of tacit knowledge while others might be better at facilitating communication of explicit knowledge. Bloodgood and Salisbury (2001) supported the same notion when they identified Decision Support Systems (DSS) and Expert Systems (ES) among the technologies that could help codify knowledge, and identified communication technologies that could facilitate identification of the expert who is seen as the embodiment of the tacit knowledge. Gunter and Butler (1999) reported, in a case study of two companies, that the internet and groupware were two important IS technologies supporting a collaborative KM initiative. Corso and Paolucci (2001) found that size of the company impacted adoption rates of IS technologies in the context of knowledge transfer in New Product Development teams. They also found that companies which focused on the reuse of existing knowledge were more inclined to use databases and networked computers while companies that focused on recombination of knowledge for new solutions were more inclined to use communication channels. El Sawy et al. (2001) conducted a case-study which suggests that in order to enhance innovation, companies should provide a number of alternative IS technologies, a notion also supported by Skyrme and Amidon (1997). Steinmueller (2000) suggested that the role that IS technology has in the codification of the knowledge of an individual is relatively modest, while the major contribution might be seen in capturing the knowledge of the group, specifically the processes of the group. Ravichandran and Rai (2003) found evidence for the positive relationship between knowledge embedded in a process, by means of work routines, methods, and procedures while using repositories (databases, etc.) and process capability, in the context of software development.
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Earlier research (Russ et al., 2004; Russ et al., 2005) found that KB strategies showed a significant relationship with the use of IS technologies. Specifically, the studies found positive associations between the Codified strategy and the use of IS technologies, as well as between the Exploration strategy and the use of IS technologies. Robertson et al. (2001) found that Groupware had mix results when utilised in the context of new knowledge creation. This might suggest why this IS technology might be more effective in the context of Exploitation strategy than in the context of the Exploration strategy. They also found that Groupware is effective in supporting the process of knowledge creation only when the teams have temporal and special constraints. Kim et al. (2002) suggested that Enterprise Information Portals (EIP) support system functionalities that assist in developing the basis for codification of tacit knowledge and that provide for development of organisational routines, (Grant, 1996) which might support the Codification strategy. Armbrecht et al. (2001) suggested that Skill Databases will be the most sensitive IS technology to culture. They also suggested, consistent with Carrillo and Anumba, (2002), and Maier and Remus (2002), that the most valuable knowledge is the tacit knowledge in individuals’ heads, and that Skill Databases are extremely valuable in identification of where this expertise resides. Maier and Remus (2002) suggested that Skill Databases were a central IS technology for successful process oriented strategies. Earlier research (Russ et al., 2005) found that the investment in IS technologies in the context of KB strategies have mixed outcomes at best. No significant relationship was found between the use of IS technologies and earnings growth, profitability, or profitability growth. The only evidence that showed support involved the relationship between the Portal IS technology and earnings per employee. Russ et al. (2004) has found more significant results while testing process and product outcomes (see below). The study suggests that, with regard to Process outcomes, Knowledge Portals, and Groupware, technologies have positive and direct association with the outcomes. There were also synergistic effects between the IS technologies and the KB strategies, as well as, synergistic effect on culture, specifically values (see below) with Knowledge Portals technology in the case of Process outcomes.
3
Research hypothesis
The literature reviewed above is summarised in Figure 1 and suggests the following specific hypotheses.
Knowledge-based strategies and information system technologies Figure 1
161
Research and hypothesise framework
Artifacts Values
Culture
Russ et al., 2005b KB Strategies Codification Complementary Concealment External Acquisition Exploration Product
+ Outcomes Product effectiveness Process effectiveness
–
+ H1aii
H2bii +
H1ai
-
H2ai
H2
H2bi
H1aii
H1
+
H1bii +
-
CRM
EIP/EKP
Workflow
CRM
EIP/EKP
Workflow
+
Video - DSS Groupware Confer. IS Technologies Video - DSS Groupware Confer.
+ Skill DB
Document Mgmt.
Skill DB
Document Mgmt.
+ +
3.1 IS technologies and KB strategies Earlier research (Russ et al., 2005) found that some IS technologies are more relevant than others in the context of specific KB strategies. Skill databases and CRM technologies were found to have significant positive association with Exploration strategy, and DSS have significant positive association with Tacitness strategy. Similar results are expected in this research as well. Based on the literature review mentioned above, it is expected that a number of other positive associations will be supported. As for other IS technologies not mentioned in this context, when the literature mentioned above does not suggest a specific unequivocal direction, and due to the early exploratory stage of the research, this paper will offer no specific (directional in this case) hypotheses and will state the hypotheses as ‘no association’. Hypothesis 1 •
Particular KB strategies will have a positive association with particular IS technologies.
Codification strategy Hypothesis 1ai
the Codification strategy will have a negative association with the DSS, Video Conferencing, Groupware technologies.
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M. Russ and J.K. Jones Hypothesis 1aii the Codification strategy will have a positive association with the Workflow, EKP, Skill database technologies. Hypothesis 1aiii the Codification strategy will have no association with CRM or Document Management technologies.
•
Exploration strategy Hypothesis 1bii the Exploration strategy will have a positive association with the CRM, Workflow, Groupware technologies. Hypothesis 1biii the Exploration strategy will have no association with the other IS technologies identified in this study.
•
Transparency strategy Hypothesis 1ciii the Transparency strategy will have no association with the IS technologies identified in this study.
•
Destroying strategy Hypothesis 1diii the Destroying strategy will have no association with the IS technologies identified in this study.
•
Product strategy Hypothesis 1eiii the Product strategy will have no association with the IS technologies identified in this study.
•
External Acquisition strategy Hypothesis 1fiii the External Acquisition strategy will have no association with the IS technologies identified in this study.
3.2 Outcomes, KB strategies, and IS technologies Earlier research (Russ et al., 2004) found that some IS technologies are more relevant than others in the context of specific strategies and outcomes. For example, the study found that Portals (EKP) and Groupware technologies are positively associated with the Product outcome, while the Skill Databases are negatively associated with this outcome. The research also found that Skill Databases are negatively associated with the Process outcome. Previous research (Russ et al., 2005) also found that Knowledge Portals have significant impact on outcomes. Similar results are expected in this research as well. As for other IS technologies not mentioned in this context, when the literature mentioned above does not suggest a specific unequivocal direction, no significant associations are expected.
Knowledge-based strategies and information system technologies Hypothesis 2 •
163
IS technologies will have an additional positive effect on outcomes, above and beyond the association with KB Strategy and culture.
Process outcomes Hypothesis 2ai
Skill database technology will have a negative association with process outcomes, above and beyond the association with KB Strategy and culture.
Hypothesis 2aiii Other IS technologies will have no association with process outcomes, above and beyond the association with KB Strategy and culture. •
Product outcomes Hypothesis 2bi
Skill database technology will have a negative association with product outcomes, above and beyond the association with KB Strategy and culture.
Hypothesis 2bii Portals (EKP) and Groupware technologies will have a positive association with process outcomes, above and beyond the association with KB Strategy and culture. Hypothesis 2biii Other IS technologies will have no association with product outcomes, above and beyond the association with KB Strategy and culture.
4
Research method
4.1 Sample This study used the same data and sample as described in Russ et al. (2006). The sample description and the data is summarised below and reported for reader convenience. For a more in depth discussion see Russ et al. 2006. A convenience sampling was utilised due to time, access, and budget constraints. The sample consisted of an evening MBA programme’s students, PhD programme students and alumni from a number of Mid-West academic institutions, and employees from several Mid-West business entities to whom the authors had access. The participants had, on average, more than ten years of full time employment experience and were mostly first and second level supervisors and managers. They were asked to volunteer their participation in the study. A very extensive questionnaire, requiring about 45 minutes was developed for the study.
4.2 Measures The measures (and the data/results) of KB strategy, outcomes, and culture are reproduced here for completeness purposes only. They are reproduced from Russ et al. (2006). Only the measures and the data of the use of IS technologies is reported here for the first time (are original).
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M. Russ and J.K. Jones
KB Strategy The six strategies were found to be orthogonal (Russ et al., 2006), with each one being one-dimensional. For each dimension, consistent with the preferred approach suggested by Anderson and Gerbing (1991), one measure (for each dimension) was used to provide for unidimensiality of the indicators. For more discussion about the methodology see Russ et al. (2006). The reliability found (the Cronbach’s Alpha indicator was used-as reported in Russ et al. (2006)) for each dimension was: •
for codification/tacitness
– 0.8614
•
for complementary/destroying
– 0.8835
•
for concealment/transparency
– 0.9211
•
for external acquisition/internal development
– 0.8322
•
for exploration/exploitation
– 0.8751
•
for product/process
– 0.8880
Outcomes The authors’ earlier research (Russ et al., 2004; Russ et al., 2005; Russ et al., 2006) suggested that there were two orthogonal effectiveness indicators. One that described effectiveness in product/service (‘Product’) offerings (three indicators), the other ‘Process’ indicators (five of them) described processes effectiveness. The indicators and their validation are described in Russ et al. (2006). The reliability indicators (the Cronbach’s Alpha was used-as reported in Russ et al. (2006) were: •
for product/service offering effectiveness
– 0.9331
•
for the process effectiveness indicators (productivity and work conditions improvements, decrease of complaints by customers, reduction of costs and ability to meet deadlines)
– 0.8772
Culture The same procedure as described in Russ et al. (2004) was used in this study. The values indicators were based on the discussions in De Long and Fahey (2000) and on Kluge et al. (2001). The artifacts (office space) indicators were modified from Bukowitz and Williams (1999, p.100). The reliability indicators (the Cronbach’s Alpha was used-as reported in Russ et al. (2006)) were: •
Three values that were suggested by the KM literature as vital for successful KM implementation were trust, accessibility, and relationships. Those values were measured and combined. The corresponding reliability was: Trustworthy and open culture Cronbach’s alpha
•
–
0.8899
With regard to artifacts, the research asked about how the workspace design promoted or prohibited data and knowledge flow with respect to the number of behaviours. This aspect was measured and combined with three indicators. The corresponding reliability was: Work space design Cronbach’s alpha
–
0.8708
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IS Based on earlier research (see discussion in Russ et al., 2004; Russ et al., 2005), and the authors’ experience, data was collected about the use of the following IS technologies: Enterprise Information and/or Knowledge Portals (EIP/EKP); Customer Relationship Management (CRM); Workflow; Video conferencing; Decision Support Systems (DSS); Groupware; Skill Data Base (Skill DB); Document Management solution.
5
Findings
5.1 Initial findings – statistics Traditionally, size and industry are the two control variables used in this type of research. At this stage, due to sample size, there was no intent to use industry as a control variable. The sample is typical of the Mid-west, more heavily emphasising manufacturing and financial services than the population of business establishments in the USA. The data suggests that with regard to size, the sample was more heavily emphasising the medium and larger size companies then the population of business establishments in the USA. The specific hypothesis and conclusion that are reported later have taken this issue into consideration. The conclusions of this research are limited to companies similar (industry wide and size wide) to this sample only. Since KM initiatives and the appropriate IS are mostly used within those segments of the economy, the researchers do not view this as an issue. The following reports the basic descriptive statistics of the research sample companies and the correlations of the variables measured (again, for the purpose of completeness the findings from Russ et al. (2006) are reported here).
0.061
0.146
9. Codification (Bohn* 1–8)
0 1.079
Min.
Max.
7.00
1.00
1.40
4.08
65
0.520***
0.299*
0.107
–0.091
–0.043
0.277*
0.237*
0.163
0.239*
2
7.0
1.33
1.32
4.44
65
0.333**
0.278*
0.123
–0.057
–0.243*
0.196
0.329**
0.319**
3
100.0
10.0
23.59
49.68
65
0.269*
0.488***
0.068
0.046
0.057
0.211
0.144
4
93.75
0.0
25.56
38.79
65
0.238*
0.151
–0.001
0.106
–0.104
0.058
5
N 65 65 65 65 65 65 65 65
Variable
Use of CRM (yes = 1)
Use of EIP/EKP (yes = 1)
Use of workflow (yes = 1)
Use of video conferencing (yes = 1)
Use of DSS (yes = 1)
Use of groupware (yes = 1)
Use of skill DB (yes = 1) Use of document management (yes = 1)
0.38 0.52
0.68
0.42
0.65
0.61
0.43
0.42
Mean
– –
–
–
–
–
–
–
S.D.
0 0
0
0
0
0
0
0
Min.
1 1
1
1
1
1
1
1
Max.
Significance (+p < 10%; *p < 5%; ** p < 1%; ***p < 0.1%) * Bohn, 1994 see measure description in Russ et al., 2006 and Russ et al., 2005
0.285
S.D.
Notes:
0.730
Mean
65
0.008
11. Process effectiveness (1–7)
N
–0.020
10. Product effectiveness (1–7)
Outcomes-effectiveness
–0.125
8. External acquisition (as %)
0.119
6. Complementary (as %) –0.116
0.037
5. Concealment (as %)
7. Product (as %)
0.070
4. Exploration external (as %)
Strategy
–0.090
3. Artifacts (1–7)
1
66.0
0.0
16.70
25.61
65
0.306*
0.071
–0.023
0.092
–0.137
6
95.00
0.0
22.80
49.03
65
–0.102
0.044
–0.057
0.078
7
86.67
2.33
18.18
40.54
65
0.067
–0.257*
0.123
8
7.0
2.0
1.52
4.63
65
0.423**
0.216+
9
6.33
1.67
1.13
4.51
65
0.318*
10
7.0
2.20
1.03
4.74
65
11
Table 1
2. Values (1–7)
Culture
1. (Log of #)
Company size
Variable
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Descriptive statistics
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167
5.2 Findings – relationships summary The first hypothesis suggests that particular KB strategies will have a positive association with particular IS technologies. Due to sample size constraints each one of the IS technologies was tested individually with each one of the KB strategies by using ANOVA. Table 2 (see below) reports the results for all the analysis by strategy and IS technology. For completeness purposes and consistent with the framework described above, the researchers also report the results for the cultural indicators, the size indicator, and the outcome indicators below in Table 2. Only the significant results are reported. Researchers interested in the complete results are encouraged to contact the first author. First, the Codification strategy (Hypothesis 1a) was found to have significant positive association with EKP, Workflow, DSS, Groupware, and Document Management technologies, but no significant association with CRM, Video Conferencing, and Skill Database technologies. As such, the first three hypotheses are only partially supported. Second, the Exploration strategy had no significant association with any IS technology. As such, the first (Hypothesis 1bii) hypothesis is rejected while the second hypothesis (Hypothesis 1biii) is accepted. Third, the hypothesis (Hypothesis 1ciii) regarding the Transparency/Concealment strategy is mostly accepted, since only the Workflow technology had a significant positive association with the Transparency strategy. Fourth, the hypothesis (Hypothesis 1diii) regarding the Complementary/Destroying strategy is accepted, since no IS technology had a significant positive association with this strategy. Fifth, the hypothesis (Hypothesis 1eiii) regarding the Product/Process strategy is accepted, since no IS technology had a significant positive association with this strategy. Lastly, the hypothesis (Hypothesis 1fiii) regarding the Internal Development/External Acquisition strategy is accepted, since no IS technology had a significant positive association with this strategy. As suggested by the literature and by the previous study (Russ et al., 2005), the size of the company makes a difference. Five of the eight IS technologies are significantly positively related to the size of the company. Only CRM, EKP, and DSS are not related. Regarding culture, only the ‘Artifact’ variable is related significantly and positively and only with the DSS technology. Finally, both ‘Process’ and ‘Product’ outcomes are positively associated with the Groupware technology and the ‘Process’ outcome is also associated with the DSS technology. The next part of the study was the exploratory research of the relationship that the KB strategies might have with outcomes. As mentioned earlier, the study controlled for organisation size and for culture. The size had no significant relationship with any of the factors. Regardless, size results are reported in the findings.
Notes:
0 = 4.085* 1 = 4.952
1 = 5.06
1 = 44.55
0 = 28.33**
0 = 4.527* 1 = 5.034
1 = 4.913
1 = 4.732
0 = 4.00**
1 = 4.910
0 = 3.977*
0 = 4.381*
1 = 5.190
0 = 4.195**
1 = 4.891
1 = 0.781
1 = 0.750
1 = 0.800
Groupware 0 = 0.626*
0 = 4.133*
DSS
0 = 0.450***
Video conferencing
0 = 0.624*
Workflow
0 = 3.843*
EIP/EKP
Significance (*p < 5%; **p < 1%; ***p < 0.1%)
11. Process effectiveness
10. Product effectiveness
Outcomes-effectiveness
9. Codification
8. External acquisition
7. Product
6. Complementary
5. Concealment
4. Exploration external
Strategy
3. Artifacts
2. Values
CRM
1 = 0.820
0 = 0.678*
Skill DB
1 = 5.153
0 = 4.024**
1 = 0.836
0 = 0.617**
Document management Table 2
Culture
1. (Log of #)
Company size
Variable
168 M. Russ and J.K. Jones
IS technologies and culture, KB strategies ANOVA
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169
The second hypothesis suggested that IS would have a positive and significant relationship (above and beyond culture and strategy) on outcomes. Due to sample size constraints each one of the IS technologies was tested individually. The ‘Process’ outcome for the DSS and Groupware technologies were also tested together, since earlier (see Table 2) both of them were found to be significantly related to the outcome (but not here, see Model III in Table 3). Only one IS technology (Groupware) showed a statistically significant association (see model III in Table 4) with the ‘Product’ outcome above and beyond the KB strategies (researches are welcome to contact the first author for the results of the other IS technologies not reported here). As such, the two hypotheses regarding the Skill database (Hypotheses 3ai and 3bi) were rejected. The only hypothesis (Hypothesis 3bii) that predicted positive association is partially supported, since Groupware is associated with the outcome, but EKP is not. The other two hypotheses (Hypotheses 3aiii and 3biii) that suggested no association were supported as well. Table 3
Outcomes and culture/KB strategies/IS technologies (Process effectiveness)
Outcomes Model
Process effectiveness II
III
2.471*** (0.546)
1.681* (0.674)
1.716* (0.727)
0.102 (0.399)
–0.255 (0.380)
–0.365 (0.408)
Values
0.353*** (0.080)
0.275** (0.080)
0.262** (0.084)
Artifacts
0.180* (0.087)
0.082 (0.191)
0.069 (0.094)
Exploration external
0.005 (0.005)
0.005 (0.005)
Concealment
0.004 (0.004)
0.004 (0.004)
Complementary
0.010 (0.006)
0.011 (0.007)
Product
–0.001 (0.005)
–0.001 (0.005)
External acquisition
0.001 (0.006)
0.001 (0.006)
Codification
0.246*** (0.067)
0.236** (0.073)
Intercept
I
Controls Company size (log of #) Culture
KB strategies
IS Technology Groupware DSS
0.174 (0.240) 0.056 (0.229)
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M. Russ and J.K. Jones
Table 3
Outcomes and culture/KB strategies/IS technologies (Product effectiveness) (continued)
Outcomes
Process effectiveness
Model R Square R Square adj.
I
II
III
0.332
0.496
0.505
0.30
0.415
0.403
6.132***
4.925***
10.274***
F Notes:
Significance (+p < 10%; *p < 5%; **p < 1%; ***p < 0.1%)
Table 4
Outcomes and culture/KB strategies/IS technologies (Product effectiveness)
Outcomes Model
Product effectiveness I
II **
III
2.882 (0.675)
2.855 (0.798)
2.934*** (0.796)
–0.051 (0.520)
–0.462 (0.471)
–0.707 (0.475)
Values
0.198+ (0.099)
0.114 (0.093)
0.069 (0.094)
Artifacts
0.194+ (0.108)
0.052 (0.106)
0.039 (0.104)
Exploration external
0.022*** (0.006)
0.023*** (0.006)
Concealment
0.004 (0.005)
0.003 (0.005)
Complementary
–0.001 (0.008)
0.001 (0.007)
Product
0.003 (0.005)
0.004 (0.005)
External acquisition
–0.019** (0.007)
–0.019** (0.007)
Codification
0.162* (0.079)
0.134+ (0.079)
Intercept
***
Controls Company size (log of #) Culture
KB strategies
IS Technology 0.547* (0.271)
Groupware R Square
0.134
0.419
0.463
R Square adj.
0.092
0.323
0.361
F
3.171*
4.40***
4.563***
Notes:
Significance (+p
