Knowledge Management Strategy: An Organizational ...

Journal of Enterprise Information Management Knowledge Management Strategy: An Organizational Change Prospective Muhammad Kashif Imran Ahmad Raza Bilal Usman Aslam Ubaid Rahman

Article information: To cite this document: Muhammad Kashif Imran Ahmad Raza Bilal Usman Aslam Ubaid Rahman , (2017)," Knowledge Management Strategy: An Organizational Change Prospective ", Journal of Enterprise Information Management, Vol. 30 Iss 2 pp. Permanent link to this document: http://dx.doi.org/10.1108/JEIM-10-2015-0095

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Knowledge Management Strategy: An Organizational Change Prospective Purpose The most critical phase of a change process is change implementation and it is evident that masterfully originated change process fails due to its poor implementation. Therefore, this study aims to profile how Knowledge Management (KM) strategies, personalization & codification, are helpful in successful change implementation by reducing the employee cynicism and increasing the level of readiness for change.


Methodology With temporal research design, 196 employees and executives of national bank of Pakistan completed

questionnaires

at

both

Time

1

(pre-implementation)

and

Time

2

(post-implementation). Multiple regression analysis was done to check the direct effect, Preacher and Hayes (2004) test was applied to measure the mediating effect and guidelines of Aguinis (2004) were followed to analyze the moderating effect. Results The results of the direct effect revealed that KM strategies, personalization & codification, have significant positive effect on successful change implementation. Further, mediation analysis proved that readiness for change is partially mediated the relationship in between KM strategies and successful change implementation success. Moreover, weakening effect of employee cynicism was observed in between readiness for change and successful change implementation relationship. Implications The management has to initiate steps to boost personalization and codification strategies at their optimal levels that will ultimately helpful to implement a change successfully through developing readiness for change and reducing the employee cynicism regarding change. Originality/value It is evident from existing literature that successful change implementation has not yet explored in the context of KM strategies.

Key words: Knowledge Management Strategies, Personalization, Codification, Readiness for Change, Employee Cynicism, Successful Change Implementation.

Introduction: Dynamism for organizations prevails in local and global markets that ultimately become cause for maintaining a constant change to align organizations with market demands and remain alive in respective industry (Elrod and Tippett, 2002). Change is the only phenomenon that is constant in all types of vital organizations as organizations are continually changing their strategies, culture, structure & processes to line-up with their capabilities within the industry (Batra and Magala, 2016, Wu et al., 2011). Additionally, change becomes an essential element of day-to-


day life of the organizations in trade free zones (Brown and Cregan, 2008). Therefore, change gathered a considerable attention from academia side as well; researchers theoretically and empirically tested change theories that are based on cultural, rational, political and technical nature (Finney and Corbett, 2007, Jones et al., 2005, DiClemente et al., 2004, Tenkasi and Chesmore, 2003, Adil and Magala, 2016). Further, every change faces cynicism, organization wide and employee oriented, from planning to implementation phase (Eby et al., 2000). Likewise, if employee cynicism persists long time in transition phase of change, it will lead to failure in implementing change as employees are performing two main functions in organizations, decision making and information sharing (Weick and Quinn, 1999). Therefore, previous literature showed a considerable thoughts to address the intellectual capital traits towards change (Andersson, 1996, Bommer et al., 2005, Maimone and Sinclair, 2014).

Hence, to see the importance of change, organizations emphasized on pre-implementation phase of change and articulated the issues that cause failure to change implementation (DiClemente et al., 2004, Beycioglu et al., 2014). Here, readiness for change recognized as major factor that has maximum variation towards change implementation (Carlon et al., 2012). Readiness for change can perform the key role for successful implementation of change through addressing motivation for change, proper disclosure of change benefits towards staff growth, and adequacy of resources for proper implementation of change (Lehman et al., 2002). Additionally, readiness for change phase took its time due to its importance towards successful implementation of change and also emphasized on effective information sharing that is beneficial for change process (Cunningham et al., 2002). Likewise, through proper and timely information sharing regarding risks and benefits associated with anticipated change, employee cynicism can be reduced and change is implemented as anticipated (Eby et al., 2000).

For creation of effective readiness for change, the role of change initiators and implementers has utmost vital (Ribeiro Soriano et al., 2012). Additionally, their knowledge level regarding the parameters of change and what knowledge management strategy they opt to disseminate their knowledge regarding change is also important (DiClemente et al., 2004). Either, they personally visit employee-to-employee or in group form, elaborate material regarding change and facilitate the employees until they used to do work in change environment, that is known as personalization strategy (Hansen et al., 1999, Scheepers et al., 2004, Ajith Kumar and Ganesh, Downloaded by University of Newcastle At 06:58 27 January 2017 (PT)

2011). Conversely, they communicate the change process centrally and through handouts regarding the change by which employees get information and implement change, that is codification strategy (Hansen et al., 1999, Scheepers et al., 2004, Ajith Kumar and Ganesh, 2011). Further, researchers theoretically found that many organizations adopted optimal mix of knowledge management strategies, personalization and codification to respond a particular situation (Cole et al., 2006).

In view of extant literature, lacking of adequate knowledge at planning phase of change restricts its further viability and if these types of change are formed and implemented then may lead to failure (Hansen et al., 1999). Despites of its significance, a rare work is done on knowledge management in context with change; however, some researchers found a facilitating link of knowledge management tools toward effective change (Burton-Jones, 2001, Pan and Scarbrough, 1999, David and Fahey, 2000, Davenport and Guest, 2001) but no one check the direct or indirect effect of knowledge management strategies on successful change implementation.

Based on this gap, this paper strives to profile the potential impact of knowledge management strategies, personalization and codification, on successful change implementation. Further, researchers have examined the benefits of these two knowledge management strategies in a change process of an organization. This paper also empirically tests the extent of which readiness for change mediates the relationship between knowledge management strategies & successful change implementation. Further, this study examines whether employee cynicism moderates the relationship between readiness for change and successful change implementation. This research

introduces a new mantra for organizations regarding successful change implementation through effective use of knowledge management strategies and contributes to change without pain.

Literature Review:

Readiness for Change: A historic study by Armenakis et al. (1993), theoretically expressed the concept of readiness for change as the perception of employees towards change and their attitudes, behaviors and Downloaded by University of Newcastle At 06:58 27 January 2017 (PT)

intentions regarding prospective change. Armenakis et al. (1993) differentiated the concepts of readiness for change and resistance to change in an organizational context and explained the importance of readiness for change to cope-up the problems of resistance to change. After them, other researchers analyzed the vitality of the readiness for change in context with expected and on-going change (Hunter and Timme, 1991, Cunningham and Hyman, 1995, McNabb and Sepic, 1995, Armenakis and Bedeian, 1999, Weick and Quinn, 1999, Eby et al., 2000, Cunningham et al., 2002, DiClemente et al., 2004, Brown and Cregan, 2008, Latta, 2015, Carlon et al., 2012). Formation of change readiness is not an easy task for organizations (Brown and Cregan, 2008), Likewise, it becomes a complicated task in current dynamic era when change is going to take place at every moment (Jones et al., 2005). When we are concerned with readiness for change, then, it is worth mentioning here that this phase is different from business to business and industry to industry (Adil and Magala, 2016). Volatility of business decides the time span of readiness for change phase, more volatile a business less time needed for readiness for change phase and vice versa. Jones et al. (2005) worked out the ratio of successful change implementation and role of readiness for change phase and suggested that if readiness for change phase is truly organized, it will definitely lead to successful change implementation. Although, there is great significance of readiness for change towards change implementation but organizations are confused about how to maintain proper readiness for expected change (Lehman et al., 2002).

Knowledge Management Strategies and Readiness for Change: Knowledge management is not a new subject in the business world but current era gives this name to some old practices, i.e. when a goldsmith gave training to his son, today we knowthis

practice as personalization strategy and small business plans were shared through letters, that is now termed as codification strategy(Hansen et al., 1999). Knowledge has two broad types, tacit knowledge, that is intellectual one and property of the individuals, other one is explicit knowledge, which is publically available in published form.There are two main strategies of knowledge management discipline i.e. personalization and codification (Ajith Kumar and Ganesh, 2011, Earl, 2001, Scheepers et al., 2004).Knowledge management strategies, personalization and codification, revolves between these two types of knowledge(Ajith Kumar and Ganesh, 2011). Personalization strategy used people-to-people method for exchange of Downloaded by University of Newcastle At 06:58 27 January 2017 (PT)

knowledge and it is very older method(Davenport and Guest, 2001, Hansen et al., 1999). On the other hand, codification strategy used people-to-document and document-to-people strategy. In codification strategy, a central repository is used to collect all relevant information and all authorized is free to access this repository any time(Hansen et al., 1999, Scheepers et al., 2004). Different studies have explained KM strategies as of two types; codification & personalization (Hansen et al., 1999, Scheepers et al., 2004). Moreover, Earl (2001) and Desouza and Evaristo (2004) explained a hybrid approach for managing knowledge in organizations instead of relying on single strategy.Scheepers et al. (2004) have developed model of organizational capabilities through knowledge management strategies. Readiness for change is a form of organizational capabilities that gives a platform to management to implement change with less resistance (Elrod and Tippett, 2002).

Successful Change Implementation, KM Strategies and Readiness for Change: Without question, the most important for organizations is to implement change in an effective manner

during

change

process(Armenakis

and

Bedeian,

1999).

Successful

change

implementation refers to the state, after transition phase, at which organizations are capable of doing routine tasks as they were doing previously before applying change (Armenakis and Bedeian, 1999, Beycioglu et al., 2014, Jacobs et al., 2013). Implementing change depends on various factors i.e. how employees perceive change, employees reaction to change, change cynicism, intellectual capability of the change agents and organizational infrastructure (Cunningham and Hyman, 1995, Finney and Corbett, 2007, Jones et al., 2005).Likewise, execution of change really matters when organizational context is dynamic because organizations have to execute this step in their routine work(Weick and Quinn, 1999).

Additionally, the importance of expected change increases the intensity of implementation (Finney and Corbett, 2007). On the other hand, intellectual capability of organizations is really important for effective change implementation. Likewise, knowledge resources the organization have, skills and competencies of change implementers have positive association with successful change implementation (Scheepers et al., 2004). Knowledge management strategies provide numerous tools to develop a positive change and its useful implementation. Knowledge management strategies work by providing guidance to human resource either person-to-person or person-to-document to understand the expected change and for its rigorous implementation Downloaded by University of Newcastle At 06:58 27 January 2017 (PT)

(Hansen et al., 1999).Jones et al. (2005) explained the worth of readiness for change in a change process and its ultimate benefits at the time of change implementation.

In this study, successful implementation of change was operationalized on the basis of system usage and user satisfaction as both are the basic criteria for measuring the success of a change process.Jones et al. (2005) defined user satisfaction as the extent of which user is satisfied from new system and system usage means how much effort is required to interact with new system. The complete analysis of these two, system usage and user satisfaction, gives a clear picture of success of current change process. Based on above discussion, following hypotheses are drawn:

H1: Personalization strategy has positive impact on successful change implementation. H2: Codification strategy has positive impact on successful change implementation. H3: Readiness for change mediates the relationship between personalization strategy and successful change implementation. H4: Readiness for change mediates the relationship between codification strategy and successful change implementation.

Employee Cynicism, Readiness for Change and Successful Change Implementation:

A well-validated research on employee cynicism, Andersson (1996) defined it as the degree of resistance and dislike position resulting from hopelessness, disillusionment and frustration from employee side that cause harm to organization. From last two decades, employee cynicism attained extensive attention of researchers (Andersson, 1996, Hansen et al., 1999, Fui-Hoon Nah

et al., 2001, Elrod and Tippett, 2002, Brown and Cregan, 2008, Chiaburu et al., 2013) due to its significance in organizational routine matters that ultimately leads to overall success of the organizations. Fundamentally, employee cynicism is the outcome of losing a comfort zone that was the strength of particular employee (Brown and Cregan, 2008, Chiaburu et al., 2013, Nesterkin, 2013, Neves, 2012). Bommer et al. (2005) argued that effects of cynicism were have the detrimental reflections on employee motivation and employee performance in a particular context. Over time, meaning of employee cynicism has refined and researchers bifurcated cynicism responses with non-cynicism responses of employees(Brown and Cregan, 2008, Downloaded by University of Newcastle At 06:58 27 January 2017 (PT)

McNabb and Sepic, 1995, Li et al., 2011).Lehman et al. (2002) suggested that maximum part of developing readiness for change deals with removing the bottlenecks of expected employee cynicism.

Literature regarding organizational and employee cynicism has evident that cynicism can create interactive effect (Hochwarter et al., 2004, Neves, 2012, Li et al., 2011, Barton and Ambrosini, 2013, Shahzad and Mahmood, 2012, Brandes et al., 2007) on different organizational variables i.e. work deviant behavior, job related outcomes, organizational commitments, business strategy, employee turnover attention. Likewise, Stanley et al. (2005)explained that employee cynicism is one of the main resistors to organizational change. The critical discussion on employee cynicism, readiness for change and successful change implementation revealed the following hypothesis:

H5: Employee cynicism moderates the relationship between readiness for change and successful change implementation.

Research Model:

Insert Figure 1: Research Model Here

Research Methodology:

Organizational Setting:

The circumstance for current research was at National Bank of Pakistan (NBP), a large public sector bank of Pakistan, which has implemented a new operating system named as Core Banking Application (CBA) or profile a year prior. In this bank, management is categorized branches as category I, II, III, on the basis of number of employees. Category I branch consists of 1-5 employees, category II 6-15 and category III 16 or more. The management is planning to implement this operating system into three phases. In first phase, it is implemented on category III branches, then in second phase on category II and lastly in category I branches. The implementation phase is prolonged due to some various technical problems. The implementation Downloaded by University of Newcastle At 06:58 27 January 2017 (PT)

of new operating system would probably influence all officers and executives of bank as they have to work with this system.

Research Design:

Depending upon the nature of the study, temporal research design is used as defined by Ancona et al. (2001) in which predicting variables (knowledge management strategies & readiness for change) are measured at Time1 (T1) before implementation and outcome & moderating variables (employee cynicism & successful change implementation) were measured at Time2 (T2) during and after change implementation. The employees are using CBA at T2 and can better elaborate their satisfaction level and system usage. The beauty of temporal design is that it can measure the data at different level and can minimize the common variance arises when we get data simultaneously at point in time but cannot overlook the causality inference (Zapf et al., 1996).

Research Philosophy and Approach:

The present research is emphasized on positivistic approach in which deductive reasoning is used for formulation and testing of hypotheses. Robson (2002) highlighted the importance of positivistic approach in cross-sectional explanatory and temporal studies and further explained the procedure how hypotheses can formulate and tested under the given literature. In current study, positivistic approach is used as recommended by Dubé and Paré (2003), with the help of adequate literature on knowledge management strategies, readiness for change, employee cynicism and successful change implementation.

Sampling Procedure & Features:

Total number of employees of NBP is 16129 in which 13928 employees belong toofficer and executive cadres that are directly or indirectly using the new operating system i.e. CBA. A total sample of 386 is selected on the basis of given population through sample size calculator1 and in lines the previous studies (Jones et al., 2005, Scheepers et al., 2004, Ajith Kumar and Ganesh, 2011). The questionnaires are distributed to 386 randomly selected employees of branches where Downloaded by University of Newcastle At 06:58 27 January 2017 (PT)

new operating system is about to implement through internal courier arrangements at T1, which are fast and accurate with the request to send these back after incorporating their views. After engaging all means (phone call & email) to increase the response rate, only 243 employees responded their views at T1. At this stage, the response rate was 63 percent, which was better to measure the given variables. After implementation of change at T2 (six weeks after T1), 243 employees are re-contacted through another questionnaire to obtain their views regarding employee cynicism and user satisfaction. Using the suggestions of Jones et al. (2005) and actual timeframe given by management of NBP to employees for completely implementing change; a six-week time period is selected for second response. Then 196 employees returned their questionnaires that reflect 81 percent response rate at T2. The overall response rate is 51 percent at both T1 & T2 and these 196 questionnaires are used for analysis.

Data Analysis Strategies:

Different types of analysis are used in this study to elaborate the exposition. First of all, reliability and exploratory factor analysis is used to see the authenticity of the data. The descriptive analysis is used to describe the demographic position of the given population. Moreover, regression and correlation tests are applied to check the hypotheses. Preacher and Hayes (2004)test is applied to check the mediation effect of readiness for change. Aguinis (2004)test is used to explain the moderating effect of employee cynicism between readiness for change and successful change implementation. 1

The sample size calculator is used the following statistical formula for sample size calculation x=Z(c/100)2r(100-r), n=N x/((N-1)E2 + x) , E=Sqrt[(N - n)x/n(N-1)] where N is the population size, r is the fraction of responses that you are interested in, and Z(c/100) is the critical value for the confidence level c.

Measures:

Multi-item scales that are already developed and tested are used to measure the constructs. The reliability of the scales are tested using Cronbach (1951) coefficient value and shown in table 1 and reflect the internal consistency of the constructs.


Codification Strategy:

Codification strategy is the first knowledge management strategy (expert-to-document) that is measured on the basis of scale developed by Ajith Kumar and Ganesh (2011). Five items scale is adopted and then adapted to measure the codification strategy. After first 50 responses, Exploratory Factor Analysis (EFA) is done and from five items, only three items are loaded at factor 1 as elaborated in Table 2. The reliability of remaining three items are 0.645 (alpha value) that is adequate according toHair et al. (2006).

Personalization Strategy:

The second knowledge management strategy is personalization strategy (expert-to-employee) that is also measured on the basis of scale developed by Ajith Kumar and Ganesh (2011). The scale is adapted according to the context of the current study and with the collaboration of the banking experts. Initially five items scale is adopted and after conducting EFA, four items is selected for final questionnaire as per factor loading (see table 2). The reliability of the finally selected four statements was 0.690that is also adequate (see table 1).

Readiness for Change: Readiness for change that is the mediating variable of the current study is measured on the basis of impressive scale developed byMadsen et al. (2005). After conducting EFA, it is found that all three items are loaded and used for final questionnaire. The scale comprises of two direct and one reverse statement to measure the readiness for change. The internal consistency is also sufficient as the alpha value is 0.639 (see table 1).

Employee Cynicism:

Level of employee cynicism is measured on the basis of scale developed by Cole et al. (2006). Basically, it is five items scale to measure the intensity of employee cynicism prevailed in an organization during change. After conducting EFA, these items reduced to four statements that are adequately loaded at factor 1. The reliability analysis is conducted before the data analysis


and it is found adequate i.e. 0.691.

Successful Change Implementation:

Successful change implementation is measured on the basis of user satisfaction scale developed by Doll et al. (1994) with respect to change that is implemented by NBP. Presently, NBP is implementing new operating system, the validity and accuracy of the system is measured by users and how much they are satisfied from the current system. The user satisfaction scale developed by Doll et al. (1994) is accurately measured the success of the new operating system. A twelve items scale is adopted and initial screening is done through EFA and only eight items are loaded that become the part of final questionnaire and used to get responses from employees and executives of NBP. The final reliability of the scale is 0.789 which is also adequate.

Results and Analysis:

This case study is conducted on National Bank of Pakistan (NBP). The main characteristics of selected sample consists of 167 males and 29 females having percentages of 85.2% and 14.8% respectively, thatare clearly indicating that NBP has male dominant financial institution. This sample characteristic isalso verifying the overall gender position of NBP. The key respondents of the current study are officers and executives that are directly affecting from the new operating system. The representative sample consists of 111 executive and 85 officer cadre employees having 56.6% and 43.4% representation respectively that are about to an equal mixture of both the stakeholders. The experience really matter while change is planned and implemented and it is observed that employees having more experience have more resistance level. The current sample

includes 41 respondents with 1-5 years of experience, 126 with 6-10, 22 with 11-15 and 7 with 16-20. The experience profile of the respondents is positive because most of the respondents are below the experience level of 10 years. With respect to age maximum respondents are lies between 20-30 years and having master or equal degree.

Reliability Analysis:


Table 1: Reliability Coefficient Cronbach (1951) Alpha Value

The foremost preliminary analysis is reliability analysis that is performed on received structured questionnaires ‘by extracting cronbach alpha values. Past studies are suggested that for a healthy data analysis these alpha values of constructs should have to show good internal consistency(Hair et al., 2006). In the perspective of acceptable internal consistency, George and Mallery (2003)explained that cronbach alpha value above 0.6 is acceptable and reliable for data analysis. It is found that the internal consistency of all the constructs lie within 0.6 to 0.8 that meet the acceptable standards.

Validity Analysis: Table 2: Exploratory Factor Analysis

As earlier, in methodology portion of the study, it is discussed that all the measurement scales are adopted and then adapted as per the real context of this study with the collaboration of banking experts. Here, factor analysis test becomes mandatory to examine the construct and convergent validity of the scales (Cudeck, 2000). In initial stage, factor analysis is done at 50 responses (both at T1 & T2) and the results showed that Factor 1 regarding personalization knowledge management strategy has five items but four items is loaded. Also, codification knowledge management strategy has initially five items but three items are loaded at factor 2. While employee cynicism has five items and four items are loaded at factor 3. Whereas, factor 4 is reflecting that all the statements of readiness for change retained successfully. Successful change implementation is measured on the basis of user satisfaction towards core banking application (profile) software and eight items are load out of twelve items. Kaiser-Meyer-Olkin

(KMO) and Bartlett test were also significant that is showing the sample adequacy for factor analysis.

Descriptive Statistics analysis:

Table 3: Descriptive Statistical Analysis

In table 3, descriptive statistics and correlation analysis are applied to extract the general Downloaded by University of Newcastle At 06:58 27 January 2017 (PT)

tendency of the data and strength of relationship among variables. The mean value showed an overall positive trend and reflects a curve that might be positively skewed curve. Further the standard deviation of the data showed a deviation of approximately 1.00 from mean that is normal in social sciences data. By using Pearson correlation analysis it is found that there were medium and strong relationship among variables (Cohen et al., 2013).

Hypothesis Testing:

Table 4: Multiple Regression Analysis Multiple regression analysis is done to examine H1 and H2acceptance/rejection; it is found that there is a positive relationship investigated between knowledge management strategies and successful change implementation. Also, the model significance value is p