FACTORS THAT INFLUENCE KNOWLEDGE

FACTORS THAT INFLUENCE KNOWLEDGE WORKER BEHAVIOUR

ASA du Toit
Centre for Information and Knowledge Management, University of Johannesburg,
PO Box 524, Auckland Park 2006, South Africa
Email: adutoit@uj.ac.za

RJ van Staden
Centre for Information and Knowledge Management, University of Johannesburg,
PO Box 524, Auckland Park 2006, South Africa


Organisations now rely on knowledge workers to take responsibility for their own career development. The demand for knowledge workers are on the increase, yet little is known with regards to their career perceptions and attitudes. This paper focuses on exploring the issues and factors affecting the career development of knowledge workers. Specialisation and dual career ladders are required to ensure that the knowledge residing in the minds of knowledge workers are not lost. A survey was conducted to determine career development opportunities for knowledge workers in South Africa. The results revealed that knowledge workers are motivated through traditional means such as money, awards and recognition, but place less emphasis on temporary assignments and mentoring than their counterparts from other countries. Organisations should leverage the knowledge contained in the minds of their knowledge workers to create a sustainable, competitive advantage.

1. Introduction
Knowledge is stored in the minds of knowledge workers, which means that organisations need to balance business needs against the needs of knowledge workers (Stokely, 2008:47), to ensure that organisational knowledge becomes a strategic asset in order to remain competitive and survive in the knowledge economy (Zack, 1999). Products, services and processes that create value are becoming more complex, requiring even more changes in the way organisational knowledge is managed. This result in changes in the way knowledge workers develop their careers and the usual lifelong career with one organisation seems to have become something of the past. The knowledge economy is forcing knowledge workers to realise that multiple assignments, projects, jobs and possibly multiple careers are the norm. Even though the knowledge economy can be turbulent, successful knowledge workers are able to see new opportunities for themselves and society (Drucker, 2001:283).
The purpose of this paper is to determine the factors affecting the career development of knowledge workers in South Africa. For a country such as South Africa this study is of extreme importance as the country is facing a serious shortage of skills. Career development of knowledge workers can create a strategic advantage for the country while correcting mistakes of the past. Using knowledge workers to the best of their abilities lead to higher productivity and efficiency which is sorely needed in South Africa. If prosperity and even survival depends on knowledge worker productivity (Drucker, 1999:83), then organisations in South Africa need to address issues concerning knowledge workers. The demand for knowledge workers are on the increase, yet little is known with regards to their career perceptions and attitudes. This paper focuses on exploring the issues and factors affecting the career development of knowledge workers. The reliance on knowledge workers creates interesting problems for a developing country such as South Africa. Specialisation and dual career ladders are required to ensure that the knowledge residing in the minds of knowledge workers are not lost.

2. Knowledge workers
Bergeron (2003:58) defines knowledge workers as individuals who contribute to the intellectual capital of their organisation. Knowledge workers are considered to be employees who employ thoughts more than manual labour in their daily tasks. The products or output of a knowledge worker is considered to be knowledge assets consisting of documentation, newsletters, online weblogs and other publications. Drucker (2002:238) defines knowledge workers from an individual’s point of view. An individual with significant amounts of theoretical knowledge and learning constitutes a knowledge worker. Paton (2005:23) defines a knowledge worker as an educated individual. The individual has been educated in a specialist knowledge area and posses theoretical, contextual or tacit knowledge. The individual is actively working in this field of specialist knowledge, all the while learning more about the field of knowledge. The authors agree that a knowledge worker is seen as an individual that has considerable knowledge and learning in a specialist field. Knowledge workers use knowledge to generate a living through thinking and not necessarily manual labour whilst taking responsibility for their own learning and development. Knowledge workers need lifelong learning and work experience to contribute to their organisation’s competitive advantage. Knowledge workers use learning and knowledge to provide their organisations with a competitive advantage and ultimately, success. In so doing, knowledge workers indirectly improve their professional performance throughout their working lives.

3. Knowledge work
The work that is performed by knowledge workers throughout their careers forms part of knowledge work. Knowledge work is discretionary behaviour and activities that are performed by knowledge workers (Efimova, 2003:1, Schell, 2008:4). Information gathering, imagination, experimentation, discovery and integration of knowledge within larger systems are all part of knowledge work (Myers, 1996:46). Technical skills, behavioural competencies and attitudes all contribute to the knowledge work that is performed (Mercer, 2008). Knowledge workers essentially think for a living, doing intangible work that is collaborative and iterative in nature in order to generate a competitive advantage for their organisation (Zuber-Skerritt, 2005:62). The skills, competencies, commitment, motivation, loyalty, creativity, education and attitude all contribute to knowledge work and are essential to knowledge management (Marr, Schiuma & Neely, 2004:562; Binney, 2001:36).

4. Demand for knowledge workers
The role played by knowledge workers is central to the competitive advantage of organisations in the knowledge economy. If we take into account that knowledge workers will become the dominant group of workers in the future (Drucker, 2002:237), then knowledge workers will appear to have borderless, upward career mobility with the potential for failure or success. The growth in certain economic sectors, coupled with knowledge workers entering retirement creates a unique demand for knowledge workers. The computer, manufacturing and education sectors are set to see unprecedented growth, requiring even more knowledge workers (Drucker, 2002:257). Such growth requires knowledge workers to acquire formal education to enter these areas of knowledge work. Once knowledge workers enter these sectors, continuing education will be required to ensure that their knowledge is kept up to date. Such a scenario highlights the need for continuous learning of knowledge workers as knowledge rapidly becomes obsolete in knowledge organisations.
The transition of knowledge workers from a young age to an older age requires succession planning to ensure that knowledge remain in organisations (Harman & Brelade, 2000:31; Stovel & Bontis, 2002:309). Succession planning for knowledge workers due to age-related factors have been ignored by organisations as they frequently only devote time and energy to managing succession and career planning of their internal elite (Holbeche, 1997:36). Proper succession planning will enable organisations to deal with the demand for knowledge workers and provide a certain level of career management for such knowledge workers (Harman & Brelade, 2000:31; Holbeche, 1997:38). Older knowledge workers (older than fifty years of age) have been noted to work in new and different ways. Frequently older workers will take on part-time assignments, work as consultants or focus on special tasks, moving away from traditional nine-to-five jobs (Drucker, 2002:235). The choices available to older knowledge workers will combine traditional and non-traditional jobs and more leisure time. As more than 25% of the working age population in the United States of America will reach retirement age by 2010 and the United Kingdom’s largest working group by age falls into the 45-59 year olds, the impact of age on the demand for knowledge workers is notable (Meister, 2005:58).
The increase in longevity of workers has also created this unique problem for organisations. Knowledge workers can no longer perform the same kind of work for fifty years. Second careers after retirement are seen as ways to keep mentally fit (Drucker, 2002:249). Becoming a freelance worker, contractor or consultant also aids organisations as new ideas and innovations can be brought into organisations as part of any knowledge worker’s job (Drucker, 1999:86; Higgins and Tap, 2008:35). Knowledge workers cannot be replaced by manual labourers as they are the only workers that can create, use and share knowledge (Malhotra, 1998). Organisations should therefore adapt their knowledge management programmes to retain key expertise in an effort to reduce costs and develop new products and services (Stankosky, 2005:150). Educated and experienced people are needed by knowledge-based organisations (Drucker, 2001:289) to create an additional advantage through knowledge workers (Drucker, 2002:88). The demand for knowledge in an industry determines the requirements for knowledge required in knowledge workers (Yang & Lee: 83). The demand for knowledge workers will increase in the foreseeable future, with a corresponding need for better management of knowledge workers. Determining what a knowledge worker is doing, compared to what they should rather be doing determines where a knowledge worker’s strengths, performance and values lie. Transforming these strengths and values into performance is to the benefit of the organisation.
5. Career development of knowledge workers
The value of knowledge workers needs to be taken into account if managers are to create the future direction of the organisation and knowledge workers have a direct influence on the future potential of the organisation (Malhotra, 1998; Mindrum, 2007:49). In the knowledge economy, individuals move frequently between jobs and even organisations, causing individuals to regard a career as a sequence of work related experiences over the course of their lives (Bergeron, 2003:593). The work experience can include any type of work, in any industry and over any length of time which is a radical move away from lifelong employment with only one employer. In order to maintain their competitive advantage, organisations need knowledge workers (Drucker, 2002:23). Attracting, retaining and motivating knowledge workers are but a small part of career issues as knowledge workers need incentives that are bigger than performance bonuses or stock options (Drucker, 2002:24). An example of an intangible incentive is to consider knowledge workers as partners in an organisation. Recognising knowledge workers as partners will help attract the best knowledge workers in a competitive job market (Binney, 2001:36). The changes in traditional organisational structures are forcing many individuals to change their view of a career as the career options in flatter organisations are limited (Evans, 2003:180). Knowledge workers need to prepare for roles in their careers and no longer jobs. Managing a career requires individuals to be flexible and to learn continuously in order to fulfil their responsibilities as the quality and nature of any career is defined by the accumulation of knowledge (Feldman, 2002:296; Koenig & Srikantaiah, 2004:523). Learning, innovation and collaboration are becoming increasingly important as part of a career management strategy as knowledge workers need more skills, education and training (Marcus & Watters, 2002:91; Winslow & Bramer, 1994:249). At the start of any knowledge career, the type of work, the financial compensation and the training on offer influence the career choices (Freeman-Bell & Balkwill, 1996:315). The productivity and quality of knowledge work is significantly impacted by these factors as individuals are the driving force behind the utilisation of knowledge (Marcus & Watters, 2002:92). The initial motivating factors play a major part in determining whether knowledge workers will start a satisfied career (Freeman-Bell & Balkwill, 1996:315).
Myers (1996:184) and Tampoe (quoted by Carter & Scarbrough, 2001:218) identified four key career motivators once a knowledge worker has moved beyond career entry. These four key motivators are personal growth, operational autonomy, task achievement and money.
Personal growth is the first key motivator and can be described as the opportunity for individuals to realise their potential through intellectual, personal and career development. Organisations need to address job design, assignments and career progress to provide meaningful and challenging work that will lead to personal growth for knowledge workers (Mercer, 2008). Knowledge acquisition forms part of personal development, leading to a sense of achievement and recognition of peers and ensures that workers grow as individuals and as professionals (Lin, Kuo, Ho & Kuo, 2008:93; Svetlik & Stavrou-Costea, 2007:197; Thite, 2004:33). The stimulation and challenges provided by the job that a knowledge worker performs also contribute to personal growth (Dovey & White, 2005:253). Knowledge workers such as software developers desire challenging work and learning opportunities (Dovey & White, 2005:253). People are motivated when they are interested in the job, even though they may find the status, perks or responsibility associated with it invaluable.
Operational autonomy is the second key motivator and can be described as a work environment that allows knowledge workers to have control over the tasks that are assigned to them within the constraints of the organisational setting. The organisational culture and leadership impact the manner in which knowledge is managed (Mercer, 2008). Knowledge workers need a dynamic knowledge-based organisation to be able to define and direct their own jobs if they are to take responsibility for their tasks (Drucker, 1999:84; Myers, 1996:46). Organisational culture needs to align itself with the values and habits of knowledge workers to provide such a level of autonomy (Nemeth & Nemeth in Nonaka & Teece, 2001:101). The key to obtaining this level of autonomy lies in the level of flexibility a knowledge worker’s manager will allow (Mercer, 2008).
Task achievement is the third key motivator and can be described as the sense of satisfaction that a knowledge worker gets from producing work of a high standard and quality that the individual feels proud of. Aligning the personal goals of knowledge workers with organisational goals will enable them to be motivated through task achievement to work towards common goals and not egotistic goals (Kelly, 2007:126). Another issue related to task achievement is the boredom associated with repetitive or less challenging tasks. Tasks need to be kept challenging in order to prevent boredom from reducing the sense of accomplishment that knowledge workers get over their working careers (Dovey & White, 2005:253; Drucker, 2001:281).
The last motivating factor is money or financial incentives and rewards. Money is seen as a reward for the contribution made by knowledge workers to the success of the organisation. Even though money cannot ensure the retention of knowledge workers, money should be structured on the way work is defined in the organisation and could include base pay, incentives, benefits and retirement funds (Mercer, 2008). The study of money as a motivational factor has always featured prominently in career studies (Petroni & Colacino, 2008:22). An interesting finding in this regard shows that male knowledge workers change jobs more often for higher pay than their female counterparts (Yang & Lee, 87).
Motivating knowledge workers will increase the feeling of knowledge workers that the organisation is helping them to attain their career goals in alignment with organisational goals (Stovel & Bontis, 2002:308). Knowledge workers need trust in their organisation if they are to stay motivated and keep on learning (Marcus & Watters, 2002:92). Continuous learning is essential in motivating knowledge workers to keep on innovating, and recognition is a very powerful motivator for knowledge workers (Harman & Brelade, 2000:49; Marcus & Watters, 2002:94).
Knowledge workers must understand their needs before starting their careers as it is different to those of general workers (Lee-Kelley, Blackman & Hurst, 2007:208). Nowadays, knowledge workers prepare for their careers through self-directed learning and further education rather than from internal career programmes in order to further their personal development (Lee-Kelley et al., 2007:208). Knowledge workers attempt to create an unbounded career by working as a free agent for any organisation in any sector. The independence and negotiation power results in a better fit between the interests of knowledge workers and the goals of an organisation as the projects are chosen in order to develop their career competencies (Tremblay, 2003:11). Working as a free agent enables knowledge workers to pursue outside interests in order to achieve a better work/life balance, with leisure time becoming more important than financial incentives (Marcus & Watters, 2002:91; Robbins, 2005:596). Attempting to predict future career trends is an imprecise science as organisations still play a very important part in the role of any knowledge worker’s career. The best solution in the foreseeable future is to develop a segmented or zigzag career, with tasks and projects defining the career path and not organisational hierarchies. Knowledge workers should evaluate their career development programme as they progress towards their career goals. Evaluation such as formal appraisal reviews should assist in assessing career goals and whether these goals have been reached within a reasonable timeframe. Shortfalls in career progressions can be remedied through additional work experiences or training and development. Knowledge workers should take an active role in developing their careers as career development is all about reconsidering where you development path will take you.

6. Survey on career development of knowledge workers

6.1 Research methodology
Knowledge workers are considered to be people with considerable theoretical knowledge and learning (Drucker, 2002:238). As such, knowledge workers are responsible for their own learning and development (Gottschalk, 2005:27), using diverse sources to acquire more information and knowledge. Even though knowledge workers may be educated in a specific knowledge area, they are continually learning (Paton, 2005:23). The knowledge economy requires knowledge workers to acquire new skills and talents (Waddock, 2007:544), in order to contribute to the organisation’s competitive advantage (Drucker, 2002:124). Knowledge workers are thus considered to be individuals partaking in some form of learning, in order to increase their knowledge. For the purpose of this survey, the part-time learners of a postgraduate course were used as a random sample of such a knowledge worker population. The respondents were all enrolled at the University of Johannesburg for the M.Com (Business Management) course. The respondents came from various backgrounds and educational levels. The sample is indicative of broad trends amongst knowledge workers in South Africa.
An online survey was chosen as the research instrument of choice as the distribution of the web address via electronic mail was seen as an appealing means of communication to knowledge workers. The online survey featured a welcome page, attempting to gain the respondent’s cooperation, providing instructions on how to complete the survey and the approximate time it would take to complete the survey (Zikmund, 2003:222). The next section of the survey focused on biographical data, such as gender and age (Welman, Kruger & Mitchell, 2005:119) using simple category scales, for example, male or female, or multiple choice, single response scales for the age groupings (Cooper & Schindler, 2003:254). The following section was divided into smaller sections, each focusing on areas that have been identified in the literature review as variables affecting the career development of knowledge workers, such as how knowledge workers develop their knowledge, what motivates knowledge workers in their careers, the readiness of knowledge workers to embark on a knowledge career, the career goals of knowledge workers, their envisaged career path, the strategies knowledge workers employ to achieve their career goals and the level of satisfaction achieved in their knowledge careers. Each section was given a rating using a five point Likert scale, in order to obtain a favourable or unfavourable response from respondents. The web address of the online survey was sent out via electronic mail to 266 respondents. Out of the 90 questionnaires completed, 8 were unusable and 82 questionnaires were usable, which resulted in a response rate of 31%.
The reliability for the sections covering knowledge, knowledge development, career motivators, career readiness, career goals, career path, career strategy and satisfaction were determined using Cronbach’s alpha test, determining whether the measuring instruments are homogenous (Cooper & Schindler, 2003:237).
The Cronbach alpha for each section is shown in Table 1:

Section Cronbach alpha
Knowledge 0.730
Knowledge development 0.683
Career motivators 0.725
Career readiness 0.754
Career strategy 0.874
Satisfaction 0.896
Table 1: Reliability
The reliability coefficient for each section is greater than 0.7, indicating a positive reliability, except for the section on knowledge development. The section on knowledge development has a Cronbach alpha of 0.683. The sections mentioned in Table 1 are thus considered to be reliable for the purpose of this survey.

6.2 Findings

6.2.1 Biographical data
The gender of the respondents that completed the online questionnaire were mostly male (69.5%) with a low response rate from females (30.5%). The age groups less than 41 years and older than 25 years provided the most responses, with the number of responses from people older than 40 years tapering off to only two people older than 55 years. The field of specialisation of the respondents was mostly predominant in the business and information technology fields. One respondent was in the educational field and the other two respondents in the logistics field. The length of employment of the respondents with their current employer is quite interesting as 47.5% of respondents have worked for their current employer for three years. The demographic data is indicative of a broad range of knowledge workers. The length of employment indicates that knowledge workers are no longer content with lifelong employment with one organisation.

6.2.2 Knowledge
The descriptive statistics related to knowledge as seen from a career perspective are shown in Table 2 with the results in percentages. The modal category for each option is shaded, with the actual number of responses shown in parentheses below the percentage value.


Totally agree Agree Neutral Disagree Totally disagree
Knowledge is a key factor in any decision made with regards to my career 31.7
(26) 47.6
(39) 12.2
(10) 8.5
(7) 0.0
(0)
Knowledge is crucial in giving me a competitive advantage in my career 58.5
(48) 34.1
(28) 6.1
(5) 1.2
(1) 0.0
(0)
My job requires more knowledge than it ever did before 47.6
(39) 32.9
(27) 17.1
(14) 2.4
(2) 0.0
(0)
The higher my level of knowledge, the more rewards I will receive 24.4
(20) 40.2
(33) 24.4
(20) 8.5
(7) 2.4
(2)
Table 2: Knowledge
Table 2 indicates that knowledge is seen as a key component in a knowledge worker’s career, with more than 58% indicating that knowledge is crucial to providing knowledge workers with a competitive advantage in their careers. The importance placed upon knowledge in career decisions is consistent with knowledge workers creating a competitive advantage in the knowledge economy through the use of knowledge (Harman & Brelade, 2000:2). The amount of knowledge required by knowledge workers’ jobs are indicative of the amount of information required by knowledge workers in the knowledge economy (Bontis, 2001:3; Deng: 174). The need for knowledge workers who are able to deal with large amounts of knowledge (Deng, n.d.:174) is acknowledge by the respondents.

6.2.3 Knowledge development
The descriptive statistics related to knowledge development as seen from a career perspective are shown in Figure 1. Figure 1 indicates that knowledge development is required by knowledge workers as 68.3% of knowledge workers believe that lifelong learning is important which agrees with learning being a lifelong process (Alley, 1999:189, Drucker, 2001:305). The majority of knowledge workers (68.3%) believe that they are responsible for their own personal development as it seems that employers are no longer willing to take this responsibility (Thite, 2004:32). The low number of knowledge workers making use of internal training (30.5%) is indicative of the low investment that South African organisations make in knowledge workers according to Smith (2008). The number of knowledge workers primarily making use of external training (64.7%) should be a cause of concern for organisations as this could indicate that organisational training and development programmes are not living up to the expectations of knowledge workers. Internal training is rarely seen as a means for gaining more knowledge and could be an indication that South African organisations do not invest in knowledge workers or that knowledge workers do not attach a lot of value to internal training. Organisations need to assess their internal training and development programmes if they are to deliver any value to knowledge workers.


Figure 1: Knowledge development

6.2.4 Career motivators
The descriptive statistics related to career motivators of knowledge workers are shown in Figure 2.
Figure 2 indicates that monetary rewards and challenging work assignments are seen as very important career motivators, followed by recognition of peers and awards. Recognition by peers is noted as an important motivator by Abdulai, Bergeron (2003:73), Defillipi, Arthur & Lindsay (2006), Drucker (2002:259) and Thite (2004:33) and is seen by 79.1% of all respondents as having some or a greater extent to their career motivations. Monetary rewards are recognised by 80.3% of respondents as a key career motivator (Myers, 1996:184) with challenging work assignments (87.6%) seen by the most respondents as having the greatest motivational factor in the careers (Dovey & White, 2005:253; Mercer, 2008). Social status and job security are considered the least important career motivators for these knowledge workers. Money is still considered to be a primary career motivator and is considered as one of the most important by respondents. This could be a cause of concern as other career motivators such as autonomy and personal growth may be considered less important than monetary rewards, impacting the competitive advantage of the organisation in a negative manner.

Figure 2: Career motivators
6.2.5 Career readiness
Totally agree Agree Neutral Disagree Totally disagree
I feel that I am in charge of my own knowledge career 36.6
(30) 54.9
(45) 7.3
(6) 1.2
(1) 0.0
(0)
I adapt to any challenges in my career 40.2
(33) 57.3
(47) 2.4
(2) 0.0
(0) 0.0
(0)
I see new technology as beneficial to my career 56.1
(46) 37.8
(31) 3.7
(3) 2.4
(2) 0.0
(0)
I have created my own knowledge career strategy 25.6
(21) 46.3
(38) 18.3
(15) 8.5
(7) 1.2
(1)
I have enough knowledge to kick off a fulfilling career 24.4
(20) 50.0
(41) 15.9
(13) 9.8
(8) 0.0
(0)
Table 3: Career readiness
Table 3 indicates that a total of 93.9% of respondents consider technology to be an important part of career readiness for knowledge workers, which is an important part of knowledge management (Carter & Scarbrough, 2001:216). The importance of a career strategy is seen as important by a total of 71.9% of respondents, which is not as seen as less important than technology, which means that knowledge workers may not yet know where they belong in their careers (Drucker, 2002:89). Respondents (74.4%) feel that they have enough knowledge to start their careers, which may be a sign of overconfidence as the skills and knowledge required by knowledge workers are continuously changing (Drucker, 2002:27).

6.2.6 Career path
Table 4 indicates that the need to become a specialist is considered important to some or a large extent by 86.3% of the respondents (No Doubt Research, 2003:3). The importance of specialist positions also correlates to the importance place on dual career ladders by 71.3% of respondents (Holman, Wall, Clegg, Sparrow & Howard, 2003:146; Petroni & Colacino, 2008:22). The need for upward career growth, whilst still enabling knowledge workers to stay in a profession without becoming a manager is thus seen as an important career path for knowledge workers. The lack of importance placed on temporary work assignments by only 12.6% of respondents could be attributed to the economic downturn, or the lack of temporary work assignments available to knowledge workers in South Africa (McKenna, 2006:11). Paulins (2008:105) noted that knowledge workers use temporary assignments as part of career preparation, yet the respondents of the study indicated that they are not interested in short work assignments. The underlying reason may be due to the fact that the respondents are mostly employed as full time workers, yet the lack of interest in temporary assignments may lead to a loss of opportunity for knowledge workers entering their careers.

Very important Important Neutral Unimportant Very un-important
Dual career ladders (managerial and professional options) 31.3
(25) 40.0
(32) 21.3
(17) 6.3
(5) 1.3
(1)
Becoming a specialist in my field of knowledge 48.8
(39) 37.5
(30) 8.8
(7) 5.0
(4) 0.0
(0)
Lifetime employment with a single organisation 3.8
(3) 6.3
(5) 32.5
(26) 41.3
(33) 16.3
(13)
A portfolio of multiple jobs with different organisations over the lifetime of my career 15.0
(12) 40.0
(32) 32.5
(26) 10.0
(8) 2.5
(2)
Temporary work assignments followed by short periods of unemployment 1.3
(1) 11.3
(9) 23.8
(19) 21.3
(17) 42.5
(34)
Table 4: Career path
6.2.7 Career strategy
Figure 3 describes the career strategy of the respondents:


Figure 3: Career strategy
Figure 3 indicates that knowledge workers feel responsible for their own careers and that they are actively trying to manage their careers through networking, experiences gained and continuous learning. The most important career strategy is the continuous learning of new skills as indicated by 88.6% of respondents. Such a strategy should result in knowledge workers reaching their long term career goals (Marcus & Watters, 2002:91; Stokely, 2008:49). The least important career strategy is seen as building a network of contacts, which is something knowledge workers need to take note of as Myers (1996:52) claims that the development of social networks is critical in boundaryless careers in order to add more value to organisations. Mentoring is an area of concern as the respondents indicated that they are not keen to consult mentors in their field of specialisation. This is in stark contrast to literature, which notes that knowledge workers need mentoring to ensure that knowledge sharing occurs (Harman & Brelade, 2000:73) in order to ensure a successful entry into the job market (Currie et al., 2006:760).

6.2.8 Satisfaction experienced as a knowledge worker
The descriptive statistics related to the satisfaction experienced in the careers of knowledge workers are shown in Table 5. Table 5 indicates that 46.2% of knowledge workers are satisfied with their careers to date, with only 19.2% being very satisfied. This means that organisations are not providing most knowledge workers with a work environment which allows knowledge workers to achieve job satisfaction (Wong, 2005:273). The majority of respondents (83.8%) indicate that they work on challenging assignments or projects and that flexible work conditions are experienced by 78.8% of knowledge workers and corresponds well to the requirements placed on knowledge workers by the new boundaryless career (Lee-Kelly et al., 2007:204; Marcus & Watters, 2002:92; Thite, 2004:37; Tomlinson:153). Most knowledge workers feel that they achieve a sense of accomplishment and are closely related to working on challenging assignments (Dovey & White, 2005:253; Drucker, 2001:281). The results indicate that knowledge workers are in fact satisfied to a large extent with their careers, yet certain areas are to be looked at in order to ensure knowledge workers stay motivated. Respondents indicated that promotions and rewards based on their knowledge are insufficient. The motivation of knowledge workers could be affected through such a lack of recognition (Defillipi et al, 2006:n.p.; Drucker, 2002:259; Holman et al., 2003:146) and as such, organisations need to assess their attempts at providing a satisfying career for knowledge workers. Respondents consider autonomy important, in order to control the tasks assigned to them within their organisation (Mercer, 2008:n.p.). Knowledge workers thus strive to create their own work environment (Arthur et al., 1999:132; Marcus & Watters, 2002:92).

Very satisfied Satisfied Neutral Dissatisfied Very dissatisfied
Being promoted based on what you know 20.0
(16) 55.0
(44) 15.0
(12) 7.5
(6) 2.5
(2)
Being rewarded for your knowledge 21.3
(17) 46.3
(37) 17.5
(14) 12.5
(10) 2.5
(2)
Flexible working conditions 40.0
(32) 38.8
(31) 15.0
(12) 6.3
(5) 0.0
(0)
The contributions made by you as a knowledge worker 37.5
(30) 48.8
(39) 7.5
(6) 6.3
(5) 0.0
(0)
Working on challenging assignments or projects 36.3
(29) 47.5
(38) 13.8
(11) 2.5
(2) 0.0
(0)
A sense of accomplishment 41.3
(33) 40.0
(32) 12.5
(10) 5.0
(4) 1.3
(1)
Opportunities for career advancement 30.0
(24) 37.5
(30) 20.0
(16) 5.0
(4) 7.5
(6)
Career progress to date 19.2
(15) 46.2
(36) 21.8
(17) 10.3
(8) 2.6
(2)

Table 5: Satisfaction experienced as a knowledge worker

7. Practical applications of the survey
The results of the online survey provide an interesting look at the unique career issues knowledge workers experience from a South African perspective. Some of the issues identified dealt with the lack of importance placed upon organisational training, the lack of interest in temporary work assignments and the low importance placed on learning from mentors. Organisations need to take note of their reward structures as knowledge workers have indicated that promotions and rewards based on their knowledge is insufficient. The means of production for knowledge workers is their knowledge, leading to high levels of job mobility. Knowledge workers are therefore not bothered to only work as employees of organisations, but to work as consultants or temporary workers. Using external knowledge workers brings specialised knowledge into organisations helping internal staff to solve otherwise difficult problems. Organisations are only useful to knowledge workers if they can acquire new knowledge through working in that organisation.
Knowledge workers play an increasingly important part in the knowledge economy and contribute to the competitive advantage and future potential of organisations. The impact made by knowledge workers in the knowledge economy has prompted management to take note of the key issues affecting knowledge workers throughout their careers. The research study explored the career issues affecting knowledge workers through their careers and focused on two major stakeholder groups: organisations employing knowledge workers and the knowledge workers themselves.
7.1 Recommendations to organisations
The findings of the study, within the research limitations described in section 7.4 suggest that organisations need to understand that:
• Knowledge workers are motivated through recognition of peers, rewards and monetary rewards, without which, knowledge workers will feel unmotivated and lack a sense of achievement necessary to excel in their careers.
• Knowledge workers see internal training programmes as incapable of delivering the training they require. Organisations should ensure that their training programmes are innovative to ensure that it responds to the demands of a knowledge economy.
• Lifelong careers with one organisation are a thing of the past, knowledge workers are more concerned with lifelong learning and experiences gained through a succession of multiple jobs in order to gain the experience necessary to provide the organisation with a competitive advantage.
• Challenging work assignments provide knowledge workers with a sense of purpose and achievement. Providing knowledge workers with a series of challenging work assignments provides knowledge workers to develop their careers through such assignments.
• The organisational lifespan is much less than the natural lifespan of a knowledge worker and knowledge workers frequently outlive the organisation they work for. Knowledge workers therefore take control of their own careers as their career consists of a series of projects or assignments, irrespective of the organisation employing them.
7.2 Recommendations to knowledge workers
The findings of the study suggest that knowledge workers need to understand that:
• Autonomy of tasks and assignments enable them to take control over tasks assigned to them. The constraints in organisations do not always allow knowledge workers the freedom to take total control of tasks assigned to them, yet knowledge workers need to adapt to their organisational culture in order to remain autonomous as far as possible.
• The responsibility for career development is a personal responsibility. Knowledge workers need to ensure that they obtain challenges that lead to a fulfilling career by getting involved in challenging work that provides learning opportunities.
• Mentors are still needed if knowledge workers are to ensure that their entry into the knowledge economy leads to a successful career. Mentoring is essential in order to ensure that opportunity is provided for individuals to convert experience into knowledge.
• The motivation required to reach organisation goals should be closely aligned to personal career goals. Such a close alignment of goals leads to a sense of task achievement for knowledge workers, resulting in a satisfying career within the organisation.
• Specialisation may be more important than loyalty to many one organisation, yet the specialist skills may contribute to the career success of the knowledge worker with that specific organisation as specialisation results in a diversity of knowledge and skills beneficial to any career.
8. Conclusion
Work provides a person with a sense of purpose, challenge, self-fulfilment, development and income to enable one to participate in other spheres of life. Knowledge of the factors and issues affecting the career development of knowledge workers is essential in order to retain, develop and motivate knowledge workers. Knowledge workers are faced with less career options due to flatter organisational structures. This survey aims to improve the career options of knowledge workers with the hope that talented people will be utilised fully and that they will experience increased job satisfaction, ending up with a rewarding and fulfilling work experience. Organisational benefits include the retention of proprietary knowledge, lower training costs, no loss of morale, lower recruitment costs and seeing a return from the investment in its workers. Motivating knowledge workers is important as they are more loyal to their field of specialisation than their employer. Knowledge workers play an increasingly important part in the knowledge economy and contribute to the competitive advantage and future potential of organisations. The impact made by knowledge workers in the knowledge economy has prompted management to take note of the key issues affecting knowledge workers throughout their careers. The major findings linked to the literature consulted indicated that even though knowledge workers require more knowledge just to enable them to perform their jobs, their knowledge still provides them with a competitive advantage in their careers and the knowledge economy. In the same manner, knowledge workers acknowledge that they are personally responsible for their own career development and attempt to ensure that they partake in lifelong learning and training. The result of being able to match personal goals with organisational goals generates a sense of accomplishment for knowledge workers, which is required to build a fulfilling career.
Working on challenging assignments generates a sense of achievement, purpose that contributes to the personal and career growth of a knowledge worker. Knowledge workers should thus seek out organisations that provide a challenging work environment that could lead to career growth. Female knowledge workers change jobs less often than their male counterparts as they do not want to risk career development by being too mobile. Similarly, female knowledge workers change jobs mostly for family reasons, such as raising children.
The research study set out to explore the issues affecting knowledge workers in a South African context. Knowledge workers make up a large percentage of the workforce in the knowledge economy, making a study such as this invaluable for organisations dependent on such workers. The career issues affecting knowledge workers were established through an online survey, providing an interesting view on the autonomy, rewards, training and progress experiences by knowledge workers in their careers thus far. This research study could be used by organisations and individuals alike, to develop measures for improving the career satisfaction of knowledge workers in the knowledge economy as these workers are important contributors to the competitive advantage of organisations in the knowledge economy.

References
Alley, L. (1999). Diverting a crisis in global human and economic development: a new transnational model for lifelong continuous learning and personal knowledge management, Higher Education in Europe, 24(2), 187-195.
Bergeron, B. (2003). Essentials of Knowledge Management. New Jersey: John Wiley & Sons.
Binney, D. (2001). The knowledge management spectrum – understanding the KM landscape, Journal of Knowledge Management, 5(1):33-42.
Bontis, N. (2001). CKO Wanted – Evangelical Skills Necessary: A Review of the Chief Knowledge Officer Position, Knowledge and Process Management, 8(1):29-38.
Carter, C. & Scarbrough, H. (2001).“Towards a second generation of KM? The people management challenge, Education + Training, 43(4/5, Available from Emerald: http://www.emeraldinsight.com (Accessed 10 February 2008).
Cooper, D.R. & Schindler, P.S. (2003). Business Research Methods. 8th edition. New York: McGraw-Hill.
Defillippie, R.J., Arthur, M.B. & Lindsay, V.J. (2006). Knowledge at Work. Oxford: Blackwell.
Deng, P.S. Applying a Market-Based Approach to the Development of a Sharing-Enabled KM Model for Knowledge-Intensive Small Firms, Information Systems Management, 25(2):174-187.
Dovey, K. & White, R. (2005). Learning about learning in knowledge-intense organisations, The Learning Organisation, 12(3):246-260.
Drucker, P. (1999). Knowledge-Worker Productivity: The Biggest Challenge, California Management Review, 41(2):79-94.
Drucker, P. (2001). The Essential Drucker. Oxford: Butterworth-Heinemann.
Drucker, P. (2002). Managing in the Next Society. Oxford: Butterworth-Heinemann.
Efimova, L. (2003). Knowledge worker paradox, The Knowledge Board. Retrieved 16 June 2008 from http://www.knowledgeboard.com/item/119378 .
Evans, C. (2003). Managing for Knowledge – HR’s strategic role. Oxford: Butterworth-Heinemann.
Feldman, D.C. (2002). Work Careers: A Developmental Perspective. San Francisco: John Wiley & Sons.
Freeman-Bell, G. & Balkwill, J. (1996). Management in Engineering. London: Prentice Hall.
Gottschalk, P. (2005). Strategic Knowledge Management Technology. Hersey: Idea Group.
Harman, C. & Brelade, S. (2000). Knowledge Management and the Role of HR: Securing competitive advantage in the knowledge economy. London: Prentice Hall.
Higgins, J. & Tapp, R. (2008). Learning When to Outsource Learning, Chief Learning Officer, 7(2):32-37.
Holbeche, L. (1997). Career development: the impact of flatter structures on careers. Oxford: Butterworth-Heinemann.
Holman, D., Wall, T.D., Clegg, C.W., Sparrow, P. & Howard, A. (2003). The Essentials of the New Workplace. London: Wiley.
Kelly, C. (2007). Managing the relationship between knowledge and power in organisations, Aslib Proceedings: New Information Perspectives, 59(2):125-138.
Koenig, M.E.D. & Srikantaiah, T.K. (2004). Knowledge Management Lessons Learned: What Works and What Doesn’t. New Jersey: Information Today.
Lee-Kelley, L., Blackman, D.A., Hurst, J.P. (2007). An exploration of the relationship between learning organisations and the retention of knowledge workers, The Learning Organisation, 14(3):204-221.
Lin, C., Kuo, T., Kuo, Y., Ho, L. & Kuo, Y. (2008). The KM Chain – Empirical Study of the Vital Knowledge Sourcing Links, Journal of Computer Information Systems, 48(2):91-99.
Malhotra, Y. (1998). Knowledge Management for the New World of Business. KM Network. Accessed 9 March 2009 from: http://www.kmnetwork.com/whatis.htm.
Marcus, R. & Watters, B. (2002). Collective Knowledge: Intranets, Productivity, and the Promise of the Knowledge Workplace. Washington: Microsoft Press.
Marr, B., Schiuma, G. & Neely, A. (2004). Intellectual capital – defining key performance indicators for organizational knowledge assets, Business Process Management Journal, 10(5):551-569.
Mckenna, C.D. (2006). The World’s Newest Profession – Management Consulting in the Twentieth Century. New York: Cambridge University Press.
Meister, J.C. (2005). Addressing the Perils of Lost Knowledge and an Aging Workforce, Chief Learning Officer, 4(3):58.
MERCER. (2008). Brainpower: Rewarding knowledge workers. Accessed 8 March 2009 from http://www.mercer.com/referencecontent.htm?idContent=1314145.
Mindrum, C. (2007). Leveraging Change to Build Productivity, Chief Learning Officer, 6(11):44-49.
Myers, P.S. (1996). Knowledge management and organisational design. Massachusetts: Butterworth-Heinemann.
No Doubt Research. (2003). Knowledge Management and the Knowledge Worker. Accessed 13 March 2009 from http://www.nodoubt.co.nz/articles/knowledgeworker.pdf.
Nonaka, I. & Teece, D. (2001). Managing Industrial Knowledge: Creation, Transfer and Utilization. London: SAGE.
Paton, S. (2005). In Search of the Knowledge Worker. Accessed 9 March 2009 from: www.hrm.strath.ac.uk/ILPC/2005/conf-papers/Paton.pdf.
Petroni, A. & Colacino, P. (2008). Motivation Strategies for Knowledge Workers: Evidences and Challenges, Journal of Technology Management and Innovation, 3(3):21-32.
Robbins, S.P. (2005). Organizational Behavior. 11th edition. New Jersey: Pearson Education.
Schell, W.J. (2008). Building a Knowledge Management Framework to Overcome the Challenges of Developing Engineering Teams in Financial Services, Engineering Management Journal, 20(1):3-9.
Smith, C. (2008). Get SA out of BEE trouble. Access 9 March 2009 from http://www.fin24.com/articles/default/display_article.aspx?ArticleId=1518-1786_2318068.
Stankosky, M. (2005). Creating the Discipline of Knowledge Management. New York: Elsevier Butterworth-Heinemann.
Stokely, S. (2008). Shiny happy people, Intheblack. 78(1):46.
Stovel, M. & Bontis, N. (2002). Voluntary turnover: knowledge management – friend or foe?, Journal of Intellectual Capital, 3(3):303-322.
Svetlik, I. & Stavrou-Costea, E. (2007). Connecting human resources management and knowledge management, International Journal of Manpower, 28(3/4):197-206.
Thite, M. (2004). Strategic positioning of HRM in knowledge-based organizations, The Learning Organization, 11(1):28-44.
Tomlinson, M. The Career Trajectories of Knowledge Workers, Organisation for Economic Co-operation and Development. Accessed 13 March 2009 from: www.oecd.org/dataoecd/35/9/2101026.pdf.
Tremblay, D.G. (2003). New Types of Careers in the Knowledge Economy? Networks and boundaryless jobs as a career strategy in the ICT and multimedia sector. Accessed 13 March 2009 from: http://hal.archives-ouvertes.fr/docs/00/19/01/24/PDF/Tremblay_2003.pdf.
Van Tonder, J. (2007). Staat se gesloer laat ekonomie ver agter raak. Accessed 9 March 2009 from: http://www.solidaritysa.co.za/Tuis/wmview.php?ArtID=997.
Waddock, S. (2007). Leadership Integrity in a Fractured Knowledge World, Academy of Management Learning & Education, 6(4):543-557.
Welman, C., Kruger, F. & Mitchell, B. (2005). Research Methodology. 3rd edition. Cape Town: Oxford University Press.
Winslow, C.D. & Bramer, W.L. (1994). FutureWork: putting knowledge to work in the knowledge economy. Toronto; MacMillan.
Wong, K.Y. (2005). Critical success factors for implementing knowledge management in small and medium enterprises, Industrial Management & Data, 105(3):261-279.
Yang, I. & Lee, S. Career Development of Female Knowledge Workers in Knowledge-Based Industries, Women’s Studies Forum. Accessed on 13 March 2009 from: www.kwdi.re.kr/data/04forum-6.pdf.
Zack, M.H. (1999). Knowledge and Strategy. Boston: Butterworth-Heinemann.
Zikmund, W.G. (2003). Business Research Methods. Ohio: Thomson South-Western.
Zuber-Skerrit, O. (2005). A model of values and actions for personal knowledge management, The Journal of Workplace Learning, 17(1/2):49-64.

KNOWLEDGE MANAGEMENT & COLLABORATION

KNOWLEDGE MANAGEMENT & COLLABORATION IN STEEL INDUSTRY: A CASE STUDY
CHAGARI SASIKALA
Deptt of Library & Information Science, Andhra University,
Visakhapatnam-530003, India
E-mail:prof.csasikala@gmail.com

In a globalized economy, business excellence can be achieved only with a strong foundation in knowledge. For this, organizations have to find effective ways to translate their ongoing experience into knowledge and disseminate the same. Further they have to collaborate with other companies in the industry for giving better products to the customers. This paper is based on a study of Knowledge Management practices in a large integrated steel company- Vizag Steel, a Govt. of India Enterprise. It emphasizes the need for reengineering KM practices in manufacturing sector to meet the challenges arising out of economic liberalization and globalization.


1.0 Introduction
"Knowledge has become the key economic resource and the dominant and perhaps even the only resource of competitive advantage.”
- Peter Drucker
In a globalized economy, knowledge is becoming the greatest asset of organizations. Organizations are recognizing that business excellence can be achieved only with a strong foundation in knowledge. Many times people do not distinguish between data, information and knowledge. Knowledge can be described as the information subjected to judgment and context, while information is nothing but the processed data and data is the unorganized and unprocessed facts and figures. Events generate data, processed data becomes information, information subjected to judgment and experimentation becomes knowledge and this experience again generates newer events. In India acquiring `Gnana' (which in Sanskrit language means knowledge) is the ultimate and the Upanishads talk of the knowledge in various terms. Kalam (2004), former President of India, observed that a knowledge society is one of the basic foundations for the development of any nation.
Knowledge Management can be defined as “a systematic process of identifying, capturing and transferring information and knowledge to help make best decision, exploit business opportunities and innovate”. It basically aims to bridge the gap between ‘what an individual knows and what he/ she needs to know’ and ‘what an organization knows and what it needs to know’.
2.0 Need for Knowledge Management (KM)
It is a well-known fact that knowledge of many is always better than individual excellence. Prusak (1996) listed the following factors which lead to the recognition and growing importance of KM:
i) The globalization of the economy, which is putting terrific pressure on firms for increased adaptability, innovation and process speed.
ii) The awareness of value of specialized knowledge as embedded in organizational process and routines, in coping with the above pressures.
iii) The awareness of knowledge as a distinct factor of production.
iv) Networked computing which enables us to work and learn with each other.
Corrall (1998) observed that the primary objective of KM is to convert human capital (individual learning/ team capabilities) to structural capital (organizational knowledge such as documented processes and knowledge bases) and thereby move from tacit to explicit knowledge and reduce the risk of losing valuable knowledge if people leave the organization.
3.0 Knowledge Management in Industry
Knowledge management had enabled many reputed companies to comprehensively change their approach and service capability both internally (towards their employees) and externally (share holders). Using vivid examples from leading Japanese companies like Honda, Canon, Matsushita and Mazda, Nonaka (1991) emphasized that making personal knowledge available to others is the central activity of the knowledge- creating company.
Buckman Laboratories, Memphis, USA based manufacturer of specialty chemicals for aqueous industrial systems can be described as the pioneer in knowledge sharing in industry. Robert (Bob) Buckman, Chairman& CEO of the company is the key architect of its successful knowledge sharing system. In March, 1992 he established the Knowledge Transfer Department with focus on ‘creating information that has value for action’. The company had received the Arthur Andersen Enterprise Award for knowledge sharing. Fullmer (1999), highlighted that K’Netix, the Buckman Knowledge Network played a key role in the company’s sales crossing $300 million by 1999 and in ‘90% culture change’.
In the oil and gas industry, Chevron emphasized the concept of ‘the learning organization’ by sharing and managing knowledge throughout the company. According to Derr (1999), former Chairman of Chevron, finding and applying new knowledge makes everyone’s work more interesting and more challenging. In 1998 the company created Global Information Link creating a single desktop and operating environment worldwide. Innovative Knowledge Management was one of the key factors in reducing the company’s operating costs by more than $2 billion per year.
Hansen and Oetinger (2001) while introducing the concept of T-shaped Managers-Knowledge Management’s Next Generation, stress that companies should utilize their intellectual resources to enable them to face an array of challenges. They also gave the following examples of KM across the world in three different sectors- Petroleum, Engineering and Steel.
Energy giant British Petroleum (BP), a company with more than one lakh employees and operations across 100 countries is well known for its knowledge-sharing practices. In 1990’s Graham Hunt was the Head of a BP petro-chemical business unit, responsible for the design and construction of a giant acetic acid plant in China. Due to the complexity of bringing such a plant on stream in 30 months time, 75 employees of BP from different parts of the world flew to China. They gave advice on technical, safety, legal, accounting and financial issues. This peer assistance enabled the project commissioning on time and within budget.
Siemens, the German MNC launched a training programme that brings high potential managers of different divisions together in small teams to solve a problem facing one of the business units. Team members work together for about a year, which includes attending several weeklong meetings at an off-site corporate campus. They then make recommendations to the business unit manager involved, who serves as the team coach during the project. Through the programme, team members develop their business skills, build informal relationships across the units and saved the company millions of dollars by solving real business problems.
Arcelor Mittal Steel, the London based world’s number one steel maker has institutionalized several simple mechanisms for sharing knowledge across their far flung units (in Europe and North / Central American, Africa, CIS countries) that could easily be implemented in companies from many other industries. One is the company’s policy on directorships, which requires the General Manager of every operating unit to sit on the board of at least one other unit. The CEOs of Germany and Trinidad plants sit on each other’s boards because they both produce long steel products - bars, rods and other structural products. This enables Arcelor Mittal’s Steel plants to adopt best practices from other plants. Managing Directors of each operating unit also have a phone meeting lasting nearly two hours. Executives report exceptions and things that in company parlance `keeps them awake at night'. In one of such tele-conferences, the Managing Director in Trinidad mentions problems he was having with a transformer that repeatedly failed. Managers in Mexico and Canada plants also had similar problems with similar transformers. The three plants ended up cooperating on trouble shooting and getting the expertise to perform repairs.




3.1 Knowledge Management In Indian Industry
In the post-independence economic history of India, 1991 was a watershed year in which wide ranging economic reforms were introduced. India has recently emerged as a vibrant free-market democracy after the economic reforms in 1991, and it began to flex its muscles in the global information economy (Das, 2002). In order to meet the challenges arising out of globalization of Indian economy, KM assumes great importance. Consequently a number of enterprises, both in private sector and public sector in India have initiated KM practices.
Larsen & Toubro, the diversified engineering giant has established a world class Technology Innovation Centre at Baroda, Gujarat state to develop new/improved processes in hydrocarbon, fertilizer, cement, power and other core industries through the use of modern technologies and sophisticated instrumentation. The Centre has linkages with Indian Institutes of Technology and research institutions like National Chemical Laboratory, Pune.
At Infosys, the Bangalore based global IT giant uses an integrated KM Strategy covering people, content and technology architecture (Kochikar, 2000). Since its inception, Infosys gave importance to learning in the organization. Its efforts to assimilate and distribute knowledge within the company began with the establishment of Education and Research Department in the year 1991. The department began gathering content and knowledge that was available within the organization and the scope of the department grew with the launch of Intranet.
A fully fledged KM programme began in 1999 with the launch of K-shop. Through K-shop, knowledge generated in each project across the global operations of Infosys was captured. Infosys was inducted into the global Most Admired Knowledge Enterprise (MAKE) Hall of Fame in the year 2005 due to its innovative KM initiatives.
Tata Steel, which has a 5 million tonne per annum capacity plant at Jamshedpur in Jharkhand state can be described as the pioneer in Knowledge Management practice in Indian steel industry. Tata Steel embarked on KM initiative in the year 1999 to systematically share and transfer learning concepts, best practices and other implicit knowledge (Mishra and Arora, 2001).
The KM system of Tata Steel underwent a lot of improvements and changes and in the process, it passed through many learning phases to reach the current state. In its latest phase, Knowledge Management has been identified as one of the key enablers to make Tata Steel self reliant in technology and will enable the company to become a truly global player.
In his pioneering study on the state of organizational culture for KM in Indian industry, Pillania (2006) emphasized the need for proper organizational culture for knowledge creation, sharing and dissemination which has serious implications for competitiveness of the firms, industry and the country.

4.0 Knowledge Management in Vizag Steel
Visakhapatnam Steel Plant (VSP) popularly known as ‘Vizag Steel’ is India’s first shore based integrated steel plant with a capacity of 3 million tonne of liquid steel per annum. The plant which became operational in 1990 is located at Visakhapatnam in the state of Andhra Pradesh, India. After a decade of turbulent times and losses, the plant got stabilized and made net profit for the first time during 2002. The company’s products enjoy market premium due to high quality and its sales turnover during 2008-09 was Rs.10,400 crores (US $ 2166 million).
4.1 Phases of Knowledge Management
Vizag Steel decided to embark on Knowledge Management (KM) initiative in the year 2001. The beginning was made in the Steel Melting Shop of the plant. Steel Melting Shop (SMS) is a core operational department of VSP, where iron (hot metal) is converted into liquid steel through LD process. Liquid steel is then made into blooms through the continuous casting process. Blooms are made as billets which are later converted as wire rods, bars, angles, channels etc. in Rolling Mills. The Steel Melt Shop has three LD converters of 150 tonne capacity each and 6 numbers of continuous bloom casters.
VSP was deep in troubled waters for almost a decade after its commissioning in 1991 and the Steel Melting Shop was the sick child of the plant, wherein Continuous Casting Department (CCD) was considered the most unreliable one. The technology was new (at that time in India only Bhilai Steel Plant was having a commissioned continuous casting shop). The employees were new with barely few experienced hands. The major problems faced by CCD were: Slide -gates, high number of breakouts, choked tundishes and bending blooms.
In its struggle to success the following changes/modifications/innovations have been done in the Steel Melting Shop.
 Russian technology on which the shop was operated was supplemented with Voest Alpine (Austria) technology, which resulted in continuous casting at higher speeds.
 For de-oxidation, Aluminum wire feeding (in place of Aluminum bars) greatly reduced running stoppers.
 Elimination of secondary oxidation and modification of tundish nozzle lead to large reduction in break-outs.
 Strict adherence of Standard Operating and Maintenance practices.
 Increased crane reliability
 Upgradation of Electrical and Instrumentation controls.
 Change in the mindset of the people on the shop-floor through a series of communication exercises and HRD programme for shop-floor employees.

The results of the above measures were extremely good as productivity has vastly improved. The average heats per day have gone up from 20 in 1992 to 62 in 2002.The Steel Melt Shop achieved the rated capacity of 3 million tonnes of liquid steel for the year ending March 31, 2002. This is the saga of `Struggle to Success' of Steel Melting Shop of VSP. The Steel Melting Shop thus played a major role in the turn around of Vizag Steel Plant.
The phases of Knowledge Management initiative at Vizag Steel are as follows:
Phase-I Phase-II Phase-III
2001-02 2002-06 2006-09
• Establishment of KM cell in SMS
• Process design
• System design • Awareness
• C o P
• Gnana Puraskar • Launch of KM portal – Gnana
• Expansion to other departments
Fig. Various phases of KM at Vizag Steel
The key drivers behind different phases of KM movement in Vizag Steel are:
• Not to reinvent the wheel - Phase-I
• Promote learning and Innovation - Phase-II
• Inventing Technology for Leadership - Phase-III

4.2 KM Strategies
Vizag Steel follows two strategies for Knowledge Management. Knowledge may be contributed by an employee (Codification) or a group of employees (Personalization). The other strategy – Knowledge distribution, derives the benefit of following the best practices identified and thus eliminating the process of ‘re-inventing the wheel’.
• Codification
• Personalization
• Knowledge Distribution
One of the objectives of Vizag Steel is to become a low cost steel producer. The company believes that this can be achieved through operational excellence besides other management strategies. The company therefore provides a platform to the employees to collaborate and contribute by each other’s experience and to innovate to achieve business excellence.


4.3 KM processes
Vizag Steel’s Knowledge Management initiatives are now coordinated by the KM group in Corporate Strategic Management Department, which facilitates knowledge generation and sharing within and outside the Company. The main processes are:
• Day to day operation
• New lessons learnt
• Cross-functional teams
• Quality Improvement Projects
• Knowledge sharing across the Division / Deptt.
• Follow-up actions for improvement
4.4 Domains of Knowledge Management
Domain knowledge can be defined as the name given to the purpose of knowledge bit (K-Bit). Each of the K-Bits given by a K-Source should have a purpose and should fit into any one of the following domains:
i. Procedures
ii. Practices
iii. Learning
iv. Root causes
v. Planning & Scheduling
vi. Success stories
vii. Systems improvement
viii. Savings

4.5 ‘GNANA’ – KM portal of Vizag Steel
Gnana, the web based KM program at Vizag Steel is an expert evaluation based system. The knowledge piece called as K-Chip submitted by an employee is automatically sent to the K-Veteran (knowledge expert) for evaluation of its quality depending on the category / sub-category chosen. After evaluation, if the K-Veteran approves the same it gets accumulated in the database as K-Asset and if it is not approved it will be turned as I-Piece. Facility is given to the K-Author for editing the I-Piece and resubmitting the same as per the guidance / comments of K-Veteran. The K-Veteran gives the rating on a 10 point scale depending on common guidelines whether the knowledge is tacit or explicit.
To recognize and reward the quality contributors to GNANA, a reward scheme “Gnana Puraskar Yojana” was launched in April 2005. So far 6000 K-chips and more than 4500 K-assets have been generated in Vizag Steel.
4.6 Community of Practice & Collaboration
Communities of Practice (CoP) are groups of people who share a passion for something that know how to do and who interact regularly to learn how to do it better .Such groups are called as “K-Groups” (Knowledge Groups) in Vizag Steel.
It is voluntary effort of people driven by the passion to excel in their work and people with similar interest and concern come together with the support of the management/superiors to enrich their knowledge through face-to-face interaction, conversations and communication. This helps the organization to create business value by breaking the silo of individual knowledge and developing group knowledge. This helps in establishing a network of people and knowledge. Ardichivili (2003) was apt in stating that when employees view knowledge as a public good belonging to the whole organization, it shows easily and trust increases knowledge sharing.
All CoP Coordinators are provided with access to update the time and venue details in the knowledge Management portal. After completion of the CoP session, the coordinator fills a standard form about the topic discussed, level of participating and future plans. They upload the presentations given at the session and add the details about the members present. This over a time became a digital library and helps others who are not able to attend a particular session to view the details and download the presentations. The attendance feed and other details available to the KM team are helpful in analyzing the progress and learning of the Communities.
As CoPs provide a platform to share experiences, learning and failures, this has helped in bringing process improvements. Some of the outcomes of CoPs in Vizag Steel are: improvement in specific energy consumption in Light and Medium Merchant Mill furnace; reduction in crane-rail consumption of Wire Rod Mill; reduction in drives’ failures etc.
Collaboration in Knowledge Management has become the sine qua non for growth and development of any industry. Collaboration can be within the organization and between organizations. According to Anklam (2002), within most companies, collaboration- co-laboring, sharing, creating something new together is the focus of several distinct type of communities, communities of learning, CoPs and communities of purpose. In situ repair of Turbo Generator-2 in Thermal Power Plant of Vizag Steel can be cited as an example of collaboration within the organization. The repair job done in 2001 was the first of its kind in steel industry in India and was accomplished with collaboration between various departments of the plant- Thermal Power Plant, Electrical Repair Shop, Central Maintenance (Electrical), Engineering Shops and Instrumentation. The total repair cost worked out to Rs.62 lakhs (US $128,000 ) in place of core replacement cost of Rs. 4 crore (US $ 830,000) and repair time was restricted to 4 months at plant site in place of 8 months at the Turbo generator manufacturer’s plant at BHEL- Hyderabad.
As regards collaboration between organizations, developing new knowledge along with competing partners is increasingly adopted in industry in order to gain a competitive advantage. Lanza (2005) stated that prior to entering knowledge based collaboration; companies should identify their coopetitors, choosing one of the following as the main goal:
• Acquiring and co-developing knowledge for a non-immediate new product development which mainly relies in knowledge exchange and sharing, whose main outcome is future technology development
• Acquiring and co-developing knowledge for a rapid market launch, aiming at knowledge creation, whose main result is a fast market entry with new products
Learning from Each Other (LEO) workshops conducted by Management Training Institute of Steel Authority of India Ltd. (SAIL) is a unique model of collaboration in KM between different organizations in steel industry in India. The Ranchi based Institute conducts the 3 day LEO workshops for shop- floor personnel of SAIL, Vizag Steel and Tata Steel. The areas covered include Coke Ovens, Blast Furnaces, Steel Melt Shop, Rolling Mills, Mechanical and Electrical Maintenance. Presentations are made by different Plants of the innovations/ modifications made and knowledge shared in respect of problems solved and benefits derived. Time bound plans are drawn up for bringing similar changes in other plants. For example, based on knowledge sharing in a LEO workshop on Reduction of failure rate of castings in the Continuous Casting Shop of Durgapur Steel Plant, a time-bound action plan was drawn up for reduction in failure rate of castings in the Continuous Casting Shop of Bokaro Steel Plant (MTI, SAIL, 2008). Though the above three steel manufacturing companies are competitors, collaboration in knowledge sharing is enabling them in technology optimization.
In order to face the challenges of globalization, growth, competitiveness and increasing knowledge content of products and services etc. Vizag Steel is striving to be a learning organization by collaboration in knowledge management. Zhujiang Iron and Steel Company (ZISCo), a Chinese state-owned enterprise encountered various challenges in 2007 particularly in the areas of Knowledge Management and development of organizational competence and learning capability (Huang, 2007). Vizag Steel, also a state owned enterprise, faced several challenges before its turnaround during 2001.These two companies with similar background may do well to collaborate for mutual benefit in Knowledge Management and organizational development.
5.0 Conclusion
Knowledge Management is a growing field in Indian industry. Thus there exist many opportunities and challenges for Indian companies in the field of KM. Creation of proper organizational culture and top management support are essential for knowledge dissemination and collaboration. Besides production and R&D, collaboration in KM, based on LEO model, can be expanded to other areas like materials and human resource management. In the technology driven global economy, effective knowledge management is the key for business excellence. As the focus is on learning organizations across the globe, there is a need for steel companies in India to reengineer their KM strategies based on the experiences of global giants like Arcelor Mittal Steel, Chevron and Siemens.

The learning from this experience of KM practices and collaboration in steel industry in India could be extended to enterprises in other core sectors of the economy - Power, Infrastructure, Heavy Engineering and Mining.

Acknowledgment
The author gratefully acknowledges the valuable inputs and suggestions from Mr. Subhendu Mohapatra, Asst.General Manager (Projects), Vizag Steel Plant in the preparation of this case study.

References

Anklam, P. (2002) “Knowledge Management : the Collaboration Thread”, Bulletin of the American Society for Information Science and Technology, 28(6): 1-8
Ardichvili, Alexander; Page, Vaughn and Wentlinge, Tim (2003) “Motivation and barriers to participation in virtual Knowledge–sharing communities of practice”, Journal of Knowledge Management, Kemptsan, 7(1):64-77
Corral, Sheila (2008) “Knowledge Management: Are we in the Knowledge Management Business?” Ariandne,18.
Das, Gurcharan (2002) India Unbound, New Delhi, Penguin Books India.
Derr, Kenneth T. (1999) “Managing Knowledge: The Chevron Way”, speech delivered at the Knowledge Management World Summit, San Francisco, CA (URL: www.chevron.com)
Fullmer, William E. (1999) “Buckman Laboratories (A)”, Harvard Business School, Boston, MA
Hansen, Morten T. and Oetinger, Bolko von (2001) “Introducing T-Shaped Managers: Knowledge Management's Next Generation”, Harvard Business Review, March :107-116.
Huang, Xueli (2007) “Strategic Management at Zhujiang Iron and Steel Company”, Hong Kong, Asia Case Research Center, University of Hong Kong
Kalam, APJ. (2004) “Challenges for Knowledge Society”, Convocation address at Bundelkhand University, Jhansi, India.
Kochikar, VP. (2000) “Knowledge – The currency of the New Millennium”,
URL: www.infosys.com
Lanza, A. (2005) “Managing heterogeneity, allocative balance and technology concerns in competitive and cooperative inter-firm relationships”, In Arturo Capasso et al. (Ed) Strategic Capabilities and Knowledge Transfer within and between organizations, 12-18, Cheltenham, UK: Edward Edgar Publishing
Management Training Institute, Steel Authority of India Ltd. Ranchi, (2008)

Mishra R. and Ravi Arora (2001) "Knowledge Management Initiatives in Tata Steel” Tata Search
Nonaka, Ikujiro (1998) “The Knowledge Creating Company”, In Knowledge Management: 21-46, Boston, MA : Harvard Business School Press.
Pillania, Rajesh K. (2006) “State of Organizational Culture for Knowledge Management in Indian Industry”, Global Business Review 7(1): 119-136
Prusak, Laurence (1996) "Why Knowledge? Why Now? ”, In: Meyers, Paul S (Ed) Knowledge Management and Organizational Design: ix-x, Newton, MA: Butterworth-Heinemann.

GUANXI, SOCIAL CAPITAL AND KNOWLEDGE EXCHANGE

GUANXI, SOCIAL CAPITAL AND KNOWLEDGE EXCHANGE: A CROSS-DIMENSIONAL VIEW
WEN TIAN
Knowledge and Innovation Management Team, USTC-CityU Joint Advanced Research Center
166 Ren’ai Road, Suzhou, 215123, P.R.China
E-mail: stellat@mail.ustc.edu.cn
FELIX B. TAN
Faculty of Business and Law, Auckland University of Technology
Private Bag 92006, Auckland 1142, New Zealand
E-mail: felix.tan@aut.ac.nz
Drawing upon the dynamics of guanxi, Nahapiet and Ghoshal’s (1998) social capital theory, and Adler and Kwon’s (2002) Opportunity-Motivation-Ability (OMA) framework, this paper develops a conceptual model to elaborate the dynamic interactions between the multi-dimensions of guanxi, social capital and knowledge exchange, and how they are influenced by the collaborative online environment in the Chinese context. We propose that the structural, relational and cognitive dimensions of guanxi are activated through the three conditions of knowledge exchange, i.e., the opportunity, the motivation and the ability, forming guanxi capital. In turn guanxi capital can lead to several types of knowledge exchange outcomes - information volume, information richness and information diversity. The dynamic process of leveraging guanxi capital to facilitate knowledge exchange is moderated by the collaborative environment, strengthened by the balance of benefits and risks evaluation of the process.
1. Introduction
The role social capital plays in facilitating knowledge exchange, combination and creation has been heavily illustrated in recent years (Nahapiet & Ghoshal, 1998; Adler & Kwon, 2002; Koka & Prescott, 2002; C.-J. Chen, 2004; Nielsen, 2005; Wasko & raj, 2005; Mu, Peng, & Love, 2008; Smedlund, 2008; He, Qiao, & Wei, 2009). Since Nahapiet and Ghoshal (1998) pointed out the three dimensions of social capital and their possible relationship to the generation of intellectual capital, the study of social capital has been very fruitful as the study of each dimension evolved. These dimensions are: the structural dimension, the cognitive dimension and the relational dimension. Studies on social network mainly address the issues in the structural dimension and those on trust and social identifications are mainly in regard to the relational dimension. However, most of these studies are conducted in a western context based on western theories, which can lead to problematic generalization of these findings to other places such as the eastern countries (Wong, Ngo, & Wong, 2003).
Close to the concept of networks in Western culture, guanxi can be viewed as a source of “social capital” (Putman, 1995) embedded in social relationships. It has a unique status in the eastern culture and has been identified as a necessary condition to do business successfully in China (Chen & Chen, 2004). Compared to social network, guanxi is more dynamic (Chen & Chen, 2004; Fu, Tsui, & Dess, 2006) and shows closer interplay with trust in knowledge exchanging activities within Chinese firms in individual level (Park & Luo, 2001; Wong et al., 2003; Chou, Cheng, Huang, & Cheng, 2006; Fu, Tsui, & Dess, 2006; Chua, Morris, & Ingram, 2009). In addition, studies on group-level knowledge transfer in the Chinese context showed that the unique Chinese cultural factors play important role in the knowledge exchange process (Hutchings & Michailova, 2006; Inkpen & Pien, 2006; Inkpen, 2008). However, the context of these studies is limited to traditional types of individual-level or group-level networks, largely ignoring the role technology plays in supporting the development of social capital and eventual knowledge exchange intentions.
In addition, there is a time dimension in both trust (Schoorman, Mayer, & Davis, 2007) and guanxi (Fu, Tsui, & Dess, 2006) Studying these at a single point of time is unlikely to discover the dynamic interactive mechanisms between trust, guanxi-generated social capital and knowledge exchange.
The purpose of this paper is therefore to develop a set of theoretical arguments and propositions in a conceptual model which synthesize the dynamic interactions between the multi-dimensions of guanxi, social capital and knowledge exchange, by clarifying the relationships between these constructs and the mechanisms by which knowledge exchange is facilitated in conjunction with the emerging online collaborative environment in the Chinese context. Based on Adler and Kwon’s (2002) “Opportunity-motivation-ability” (OMA) framework, we hope the model will provide a better understanding on how to leverage the guanxi capital to facilitate knowledge exchange in the changing business environment in China. For instance, the design and application of expert recommender systems that suggest actors to establish or to refresh relations by studying one’s guanxi network can help the system better understand whether the actor’s link to others is more common interest-oriented, or kinship-oriented, thus providing better awareness. Also, as Chinese people tend to be more willing to share in the in-group context (clan or small circle) where people have close guanxi, the design of groupware may strategically facilitate inter-group knowledge sharing to enlarge the organization’s knowledge (Hutchings & Michailova 2006).
In order to achieve the objectives, we first elaborate the rich dynamics of guanxi from previous literature, and then link the multi-dimensions of guanxi to that of social capital, so as to clarify the concept of guanxi capital in the Chinese context. Next, we examine the types of knowledge benefits generated from the creation of guanxi capital and investigate how this process would be moderated by collaborative environment. We then present the conceptual model. In the conclusion, we summarize the paper and also discuss the proposed empirical testing.

2. Literature Review
Guanxi is “by no means culturally unique” (Walder, 1986) in China. It refers to the concept of building up connections to secure favors in personal and organizational relations (Park & Luo, 2001). It has been identified as a critical condition to do business successfully (Xin & Pearce, 1998; Chen & Chen, 2004; Chua et al., 2009). Chinese people and organizations cultivate guanxi “energetically, subtly, and imaginatively” (Park & Luo, 2001), which heavily influences their attitudes toward social relationships. Even today, when information technology can lead people to whatever information they seek, guanxi informants are still a highly trustworthy knowledge source for Chinese people.
2.1. Guanxi dynamics
Trui and Farh (1997) posit that there are three types of people with whom guanxi is formed: qinren (family members), shuren (acquaintances or familiar persons such as neighbors, or people from the same village, friends, colleagues, or classmates), and shengren (strangers). Generally, the strength of the qinren guanxi is expected to be the strongest, shengren guanxi the weakest and shuren guanxi in between. However, shengren guanxi implies a “yet-to-be discovered”(Fu, Tsui, & Dess, 2006) guanxi, and Chinese people are encouraged to transform it into shuren guanxi.
On the one hand, shengren guanxi can turn into shuren guanxi or even qinren guanxi by carefully handling the interactions. On the other hand, shuren guanxi or qinren guanxi can weaken into shengren guanxi, for instance, when something undermines mutual trust. Guanxi tie changes in distance and strength in a highly contextual and relational culture like that of China, more so than may be the case in western cultures (Fu, Tsui, & Dess, 2006).
The dynamic nature of guanxi is articulated by Chen and Chen (2004) in the process of guanxi building, in which they claim that the ultimate goal is to form a long-term equity to get benefits from each other. In order to reach the ultimate goal, the three guanxi stages (i.e., the initiating, the building and the using stages) are required. But it is the use of guanxi that makes the exchange of material or spiritual matter as a desired outcome.
There are several empirical studies that shed light on how Chinese people use the dynamics of guanxi for resource exchange. For example, based on interviews with 52 managers of 16 Chinese high-tech firms, Fu, Tsui, & Dess (2006) found that guanxi categories would lead to different types of social networks that have important implications for both knowledge management and decision-making processes within firms. As for firm-level utilizations of guanxi, Xin and Pearce (1998) conducted interviews with 32 executive managers in China representing 3 types of firms and concluded that firms in different stages relied on different types of individuals’ guanxi as substitutes for formal institutional support, thus gaining resources for the firm as competitive advantages. These studies not only indicate that guanxi serves a similar function for knowledge exchange in China as that of social networks in the West, but also imply that managing the dynamics of guanxi is the key to activating the benefits of guanxi ties.
By examining the dimensions of guanxi through the lens of social capital theory, we will focus on the mechanisms that activate guanxi as a means for knowledge exchange in the following sections.
2.2. Linking guanxi to the multi-dimensions of social capital
Nahapiet and Ghoshal (1998) defined social capital as “the sum of the actual and potential resources embedded within, available through, and derived from the network of relationships possessed by an individual or social unit”. They grouped social capital factors into structural, cognitive, and relational dimensions. The structural dimension refers to the network ties, the overall configuration of these ties and the appropriable organization; the cognitive dimension include shared language and codes and shared narratives as well; and the relational dimension contains factors such as trust, norms, obligations and identifications.
As an ancient practice of social exchange (Hammond & Glenn, 2004), how does guanxi map into the social capital dimensions?
First, guanxi has many similarities with the social networks. For example, guanxi is transferable and intangible. (Park & Luo, 2001); the different types of guanxi convey different strength of the ties (Fu, Tsui, & Dess, 2006); the configuration of guanxi shows the network of the “self in relation to other” (Chou et al., 2006); and the upgrade from shengren guanxi to shuren guanxi represents how people bridge the structural holes (Bjorn & Worm, 2008).
Second, from the communicative practice point of view, the guanxi relationship based on human communication, is enabled by shared assumptions, orientations, and linguistic and extra-linguistic knowledges, which will be inherited and renewed through guanxi production (Gold, Guthrie, & Wank, 2002). Thus, guanxi is underpinned with a lot of shared codes, language and narratives.
Third, trust and identification, as in the relational dimension, are salient factors in both guanxi and social capital. Trust is a critical building block of guanxi (Park & Luo, 2001; Chou et al., 2006; Fu, Tsui, & Dess, 2006; Bjorn & Worm, 2008) and so is the case of trust to social capital in the western context (Hosmer, 1995; Putman, 1995; Nahapiet & Ghoshal, 1998; Adler & Kwon, 2002; Schoorman, Mayer, & Davis, 2007; Bjorn & Worm, 2008). In addition, the most common base of guanxi such as tongxiang, tongxue, tongshi (i.e. from the same birth place, from the same educational institution, and from the same work place respectively) consists of common social identities (Chen & Chen, 2004), while in social networks the connection to certain people or groups help people achieve social identification (Nahapiet & Ghoshal, 1998).
Based on the above, we summarize the link between guanxi and the multi-dimensions of social capital in Table 1.




Table 1 Guanxi and multi-dimensions of social capital
Social capital dimensions
(Nahapiet & Ghoshal, 1998)
Examples of Guanxi
(Chen & Chen, 2004; Fu, Tsui, & Dess, 2006)

Structural
Network ties
Network configuration Dyadic ties, distributed as an ego-centric network
La guanxi (to build guanxi) is encouraged so that guanxi network changes quickly
Relational
Trust
Identification Types of guanxi indicate different trust level:
Shengren - strangers, low trust level
Shuren - acquaintances, higher level of trust
Qinren - kinship, highest level of trustworthiness & dependency
Guanxi bases provide a high level of social identification
Cognitive
Shared codes and language
Shared narratives Guanxi production as a communication practice, shared codes, language and narratives are inherited or generated
As Table 1 suggests the key elements of guanxi are equivalent to those in social capital theory but applied a little differently. For instance, according to Fu et al. (2006), there are three main differences between Guanxi and networks. First, guanxi is usually dyadic while network involves multiple connections, because guanxi is highly particularistic between two individuals. Second, guanxi is more dynamic while network is more structured and assumed to be relatively stable once formed. Third, guanxi is much richer and more complex than networks. Not only is its inherent nature different depending on the type of people with whom guanxi is built, but also, within each category the quality of guanxi, “the state of the relationship at a given point in time” (Chen & Chen, 2004) can vary in the degree of closeness or strength (Tsui & Farh, 1997).
2.3. The OMA framework and Guanxi capital
The Opportunity-Motivation-Ability (OMA) framework, introduced by Adler and Kwon (2002), reveals the condition of how to activate social capital in that a lack of any of the three factors (i.e. opportunity, motivation and ability) will undermine social capital generation. Social structures are treated as antecedents of the three factors in this framework, and social capital benefits and risks as consequences.
Because the value of social capital lies in the “utilization” of social structures and “mobilization” of assets (Nahapiet & Ghoshal, 1998), the idea of activating social capital makes a lot of sense. Thus, we decide to wrap the “opportunity, motivation and ability” factors into the concept of social capital and into guanxi capital by the same token. Here, guanxi capital is different from merely the guanxi concept, since resources “embedded within, available through, and derived from the network of relationships” (Nahapiet & Ghoshal, 1998) must turn into actual assets to be called as capital. Adler and Kwon (2002) highlight several criteria for the resources to be characterized as capital.
However, the OMA framework does not address the relationship of the three dimensions of social capital with the OMA factors. Hence, we go back to Nahapiet and Ghoshal’s (1998) assertions and find that constructs in their conceptual model is consistent with the OMA factors in Alder and Kwon. For instance, “access to parties for combining/exchanging intellectual capital” is the opportunity for knowledge exchange, the motivation to combine/exchange intellectual capital is the same motivation mentioned in OMA framework, and the combination capability maps well to the ability in OMA framework. Aligning both the dimensions of social capital and the OMA framework has support from Huysman and Wulf (2006) who also found similarities between these two approaches.
Combining the OMA framework with the arguments in previous sections, we propose that:
Guanxi capital opportunity is enhanced by manipulating the structural, relational and cognitive dimension factors to gain more access to parties.
Guanxi capital motivation becomes stronger when there’s higher level of relational dimension factors to facilitate cooperation.
Guanxi capital ability is promoted by increasing the cognitive dimension factors to make actors more capable of synthesizing the knowledge exchanged.
Guanxi capital opportunity, motivation and ability are antecedents of knowledge exchange outcomes.
2.4. The dimensions of knowledge outcomes from guanxi capital
Social capital has been found to be useful in explaining and predicting various knowledge exchange behaviors and outcomes (Law & Chang, 2008), such as knowledge transfer, knowledge creation, knowledge acquisition and exploitation, knowledge contribution and knowledge synthesizing. The complexity of knowledge exchange process is not our focus, but the outcomes in terms of the quantity and quality of the exchanged knowledge are to our central interests.
The most-cited and influential distinction of knowledge is Polanyi’s identifications of two aspects of knowledge: tacit and explicit (Nahapiet & Ghoshal, 1998). Winter (1987) has used tacitness as a variable referring to the extent to which the knowledge can be codified and abstracted. However, in the analysis of network ties, these features of knowledge are missing (Moran, 2005; Wasko & Raj, 2005; Sykes, Venkatesh, & Gosain, 2009), since it is difficult to analyze the connectedness and the tacitness of the knowledge shared at the same time.
Is there a better way to measure the exchanged knowledge through social capital establishment? Koka and Prescott (2002) summarized three distinctly different dimensions of information benefits yielded by social capital: information volume, information richness, and information diversity. Information volume is highlighted by the dense network ties in which dense interactions allow significant volume of information be created and disseminated. But it could have adverse consequences such as when it is imperative to make fast decisions (Eisenhardt, 1989). Information richness emphasizes the quality and nature of information (Koka & Prescott, 2002). It is important in guanxi capital, as the closer the actors are, the richer the information they would share. It is always the rich-contextual and fine-grained information that flows (Fu, Tsui, & Dess, 2006) between the shuren and qinren guanxi or between well-established firm-level guanxi. Information diversity emphasizes the variety and to a somewhat lesser extent quantity of information that one can access through his relationships (Koka & Prescott, 2002).
As both guanxi and social networks encourage people to build relationships to bridge structural holes (Granovetter, 1982; Bjorn & Worm, 2008), information diversity is highly likely to be achieved in both context. But information volume is easier to get from dense networks than from complex guanxi network, while information richness is easier to obtain through interactions with those who are in the individual’s guanxi network. Table 2 shows the potential contribution that guanxi network and social network bring to the three dimensions of benefits. Although information and knowledge are different, we use them equivalent here since the information flow between the three dimensions of exchanged do carry certain amount of knowledge whether the tacit or explicit.
Table 2 Guanxi capital, social capital and knowledge outcomes
Indicators Information volume Information richness Information diversity
Guanxi network Distance between the actors Not necessary high high
Social network Network centrality & density high Not necessary high
Due to the fact that quality improvement is likely to be limited without quantity but quantity is no guarantee that quality will occur, we propose that:
Information volume and information diversity are positively associated with information richness.
However, there’s no priority in the three dimensions of the information, since knowledge is embedded regardless of the volume, richness or diversity dimension, people will find useful information as contextual knowledge to them through guanxi networking process.
2.5. The effects of collaborative environment on guanxi capitals and knowledge exchange
According to Law and Chang’s (2008) investigation of the literature related to the study of social capital in the area of knowledge management, few studies have applied social capital theory to contexts such as online collaborative environments. It is still unclear that how social capital is fostered and further being leveraged for knowledge exchange through individuals’ engagement in a collaborative environment. Adler and Kwon (2002) pointed out that some firms interested in fostering social capital have adopted collaborative technologies, such as shared knowledge repositories, chat rooms, and videoconferences, but these merely create opportunity; building social capital requires not only establishing more social ties but also nurturing motivation and providing resources. Hence, we argue that opportunity, motivation and ability serve as necessary conditions for guanxi capitals to be activated.
A study on the knowledge contribution behaviors in a distributed environment where contributions occur primarily through information technologies (Olivera, Goodman, & Tan,2008) suggests three mediating mechanisms: (1) awareness; (2) searching and matching; and (3) formulation and delivery. In their model, awareness is a cognitive activity through which a person recognizes an opportunity to contribute, thus generate motivation to engage in searching and matching; searching and matching require relevant ability while provides motivation to engage in formulation and delivery, which is a cognitive representation of the contribution. Although the context is very special, this result indicates that information technology can enhance individuals’ awareness of knowledge contribution opportunity, increase searching, matching, formulation and delivery ability of tacit knowledge, thus generating the motivation to contribute. Therefore, we argue that information technology supported collaborative environment serves as a moderator in general. The effects of collaborative environment are interpreted as follows.
For guanxi network that already exists, collaborative environment moderates the relationship between the opportunity-motivation-ability factors and knowledge exchange by enhancing actors’ capability and flexibility of managing the large volume and multiple sources of information (eg., by tracing the transaction memories).
For guanxi network yet-to-be built, the role of collaborative environment are three fold.
First, it moderates the relationship between the structural dimension and opportunity by increasing opportunities to know people (eg., increasing awareness of opportunity through “people you might know” or “people who have done xxx” recommender system). Second, it moderates the relationship between relational dimension and motivation by enhancing the fairness of the control system and protection of intellectual property so that the users’ extrinsic motivations are aroused. Third, it moderates the relationship between cognitive dimension and ability by self-disclosure of “what I’ve done” (transaction memory) and “what I know” (users’ profile), as a result those who are looking for guanxi will cognitively feel much easier to identify “shared codes” out of the system.
Therefore, we propose that:
In the guanxi network maintenance stage, the presence of collaborative environment will facilitate the management of information, thus moderating the relationship between an actor’s guanxi capital opportunity-motivation-ability factors and his knowledge exchange outcome.
In the guanxi network initiating stage, the presence of collaborative environment will provide strategies beyond traditional control of the guanxi capital dimensions, thus, moderating the relationship between an actor’s structural, relational and cognitive dimensions and his guanxi capital opportunity.
3. Conceptual Model
To activate the guanxi capital, the actor not only has to pay attention to his shuren network which provides him with the opportunity of getting access to resources, but also needs to choose the right type of shuren who has the ability to contribute knowledge, and then he can communicate with the shuren so that trust can be built during the process. When it’s all done, the guanxi capital has been activated and is ready to facilitate knowledge exchange activities. During this process, the collaborative environment such as Electronic Knowledge Repository (EKR), Knowledge Management Systems (KMS), Social Network Services (SNS), etc., can enhance the actor’s perceptions toward the opportunity, the motivation and the ability by making it more capable for the actor to manage multiple guanxi dyadic through the development of each dimension of guanxi capital. Based on previous propositions, we develop our conceptual model (Figure 1) to illustrate the process.
Although we’ve discussed a lot on the benefits of guanxi capital to knowledge exchange, guanxi is a double-edged sword which can also bring negative effects. For example, close personal connections tend to have negative externalities on organizations when people use it for private capital, rather than organizational capital (Chen & Chen, 2009). According to Adler and Kwon (2002), after the knowledge exchange activities, the actor will evaluate the benefits and risks of the process, trying to balance them. Due to the guanxi dynamics, the actor will re-evaluate the guanxi quality toward a long-term equity guanxi relationship for knowledge exchange purpose. Therefore, we add further propositions as follows:
The knowledge exchange outcomes lead to the actor’s perceptions towards the benefits and risks of the exchange process, the evaluation of which leads to the actor’s perceptions towards his guanxi capital.
4. Conclusions
The purpose of this paper is to develop a conceptual model to elaborate the dynamic interactions between the multi-dimensions of guanxi, social capital and knowledge exchange, and how they are influenced by the collaborative online environment in the Chinese context.
By examining the dimensions of guanxi through the lens of social capital theory, we firstly found that the elements of guanxi have similarities to all three dimensions of social capital. The way guanxi capital is activated is also similar to the way social capital is activated. But the nature of guanxi capital is more dynamic. Secondly, the structural, relational and cognitive dimensions of guanxi capital are positively associated to the opportunity, motivation and ability factors to facilitate knowledge exchange activities, which can result in the contribution of information volume, information richness and information diversity. Thirdly, for actors in the stage of guanxi capital maintenance, the collaborative environment moderates the relationship between an actor’s guanxi capital opportunity, motivation and ability and his knowledge exchange outcome respectively; in the guanxi network initiating stage, the collaborative environment moderates the relationship between an actor’s guanxi capital dimensions and the opportunity, motivation and ability of knowledge exchange respectively. Lastly, guanxi capital evolved as the loop from the guanxi capital building to the evaluation of knowledge exchange outcomes continues.
In terms of how the work will progress, we plan to further substantiate the relationships in the model and then empirically test these via an experiment using a recommender system. As this paper has mapped the elements between guanxi capital and social capital, we also propose to employ social networking tools used in social capital research in the experiment, so that the outcome of knowledge exchange can become more transparent - for example, to operationalize information volume, richness and diversity.
References
Adler, P. S., & Kwon, S.-W. (2002). Social capital: Prospects for a new concept. Academy of Management Review, 27(1): 17-40.
Bjorn, M., & Worm, V. (2008). Guanxi Capital as a Sustainable Competitive Advantage. In V. Worm (Ed.), China: Business Opportunities in a Globalizing Economy. Copenhagen: Copenhagen Business School Press.
Chen, C.-J. (2004). The effects of knowledge attribute, alliance characteristics, and absorptive capacity on knowledge transfer performance. R&D Management, 34(3): 311-321.
Chen, C. C., & Chen, X. P. (2009). Negative externalities of close guanxi within organizations. Asia Pacific Journal of Management, 26(1): 37-53.
Chen, X.-P., & Chen, C. C. (2004). On the intricacies of the Chinese guanxi: A process model of guanxi development. Asia Pacific Journal of Management, 21(3): 305-324.
Chou, L.-F., Cheng, B.-S., Huang, M.-P., & Cheng, H.-Y. (2006). Guanxi networks and members' effectiveness in Chinese work teams: Mediating effects of trust networks. Asia Journal of social Psychology, 9: 79-95.
Chua, R. Y. J., Morris, M. W., & Ingram, P. (2009). Guanxi vs networking: Distinctive configurations of affect- and cognition-based trust in the networks of Chinese vs American managers. Journal of International Business Studies, 40(3): 490-508.
Eisenhardt, K. M. (1989). Making fast strategic decisions in high-velocity environments. Academy of Management Journal of Business Ethics, 32(3): 543-576.
Fu, P. P., Tsui, A. S., & Dess, G. G. (2006). The dynamics of guanxi in Chinese high-tech firms: Implications for knowledge management and decision making. Management International Review, 46(3): 277-305.
Gold, T., Guthrie, D., & Wank, D. L. (2002). Social Connections in China, Institutions, Culture, and the Changing Nature of Guanxi. New York: Cambridge University Press.
Granovetter, M. S. (1982). Social structure and network analysis. In P. V. M. N. Lin (Ed.), The strength of weak ties: A network theory revisited (pp. 105-130). Beverly Hills, CA: Sage.
Hammond, S. C., & Glenn, L. M. (2004). The ancient practice of Chinese social networking: Guanxi and social network theory. E:CO Vol. 6 Nos. 1-2, 6: 24-31.
He, W., Qiao, Q., & Wei, K. K. (2009). Social relationship and its role in knowledge management systems usage. Information & Management, 46(3): 175-180.
Hosmer, L. T. (1995). Trust: The connecting link between organizational theory and philosophical ethics. Academy of Management Review, 20(2): 379-403.
Hutchings, K. and Michailova, S. (2006). Impacts of Culture and Institutions on Knowledge Sharing in Russia and China, International Journal of Emerging Markets, 1(1): 21-34.
Huysman, M., & Wulf, V. (2006). IT to support knowledge sharing in communities, towards a social capital analysis. Journal of Information Technology, 21(1): 40-51.
Inkpen, A. C. (2008). Managing Knowledge Transfer in International Alliances, Thunderbird International Business Review, 50/2, 77-90.
Inkpen, A. C. and Pien, W. (2006). An examination of collaboration and knowledge transfer: China-Singapore Suzhou Industrial Park, Journal of Management Studies 43/4, 779-811.Koka, B. R., & Prescott, J. E. (2002). Strategic alliances as social capital: a multidimensional view. Strategic Management Journal, 23: 795-816.
Law, S. P.-M., & Chang, M. K. (2008). Fostering knowledge exchange in online communities: A social capital building approach. Paper presented at the International Conference on Information Systems, Paris.
Moran, P. (2005). Structual vs. relational embeddedness: Social capital and managerial performance. Strategic Management Journal, 26: 1129-1151.
Mu, J., Peng, G., & Love, E. (2008). Interfirm networks, social capital, and knowledge flow. Journal of knowledge management, 12(4): 86-100.
Nahapiet, J., & Ghoshal, S. (1998). "Social capital, intellectual capital, and the organizational advantage,. Academy of Management Review, 23(2): 242-266.
Nielsen, B. B. (2005). The role of knowledge embeddedness in the creation of synergies in strategic alliances. Journal of Business Research, 58: 1194– 1204.
Olivera, F., Goodman P. S., Tan S. S. (2008). Contribution Behavior in Distributed Environments, MIS Quarterly, 32(1): 23-42.
Park, S. H., & Luo, Y. (2001). Guanxi and organizational dynamics: organizational networking in Chinese firms. Strategic Management Journal, 22: 455-477.
Putman, R. D. (1995). Bowling alone: America's declining social capital. Journal of Democracy, 6: 65-78.
Schoorman, F. D., Mayer, R. C., & Davis, J. H. (2007). An integrative model of organizational trust: past, present, and future. Academy of Management Review, 32(2): 344–354.
Smedlund, A. (2008). The knowledge system of a firm: Social capital for explicit, tacit and potential knowledge. Journal of Knowledge Management, 12(1): 63-77.
Sykes, T. A., Venkatesh, V., & Gosain, S. (2009). Model of acceptance with peer support: A social network perspective to understand employees' system use. MIS Quarterly, 33(2): 371-393.
Tsui, A. S., & Farh, J. L. (1997). Where Guanxi Matters. Work and Occupations, 24: 56-79.
Walder, A. G. (1986). Communist neo-traditionalism. Berkeley: University of California Press.
Wasko, M. M., & Raj, S. F. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly, 29(1): 35-57.
Winter, S. G. (1987). Knowledge and competence as strategic assets. In D. J. Teece (Ed.), The competitive challenge: Strategy for industrial innovations and renewal (pp. 159-184). New York: Harper & Row.
Wong, Y.-T., Ngo, H.-Y., & Wong, C.-S. (2003). Antecedents and outcomes of employees' trust in Chinese joint ventures. Asia Pacific Journal of Management, 20: 481-499.
Xin, K. R., & Pearce, J. L. (1998). Guanxi: Connections as substitues for formal institutional support. Academy of Management Journal, 39(6): 1641-1658.