Changing Behavior


I need help for following :

Create a 200-300-word response where you propose a plan to incentivize a change initiative within your current organization (or one with which you are familiar). You should specifically address:

  • The functional structure that best supports the organization
  • Pay for performance
  • The use of rewards (intrinsic and extrinsic)
  • Embed course material concepts, principles, and theories, which require supporting citations. 
  • Keep in mind that these scholarly references can be found in the Digital Library by conducting an advanced search specific to scholarly references.
  • This post replies need to be substantial and constructive in nature.
  •  Answering all course questions is also required.
  • Use APA style guidelines.

The below attachments are required readings:  

Knowledge network modelling to support decision-making for strategic intervention in IT project-oriented change management

Ali Alkhuraiji*, Shaofeng Liu, Festus Oluseyi Oderanti, Fenio Annansingh and Jiang Pan

Graduate School of Management, University of Plymouth, UK

(Received 10 September 2013; accepted 20 December 2013)

This paper focuses on knowledge management to enhance decision support systems for strategic intervention in information technology (IT) project-oriented change management. It proposes a model of change management knowledge networks (CMKNM) to support decision by tackling three existing issues: insufficient knowl- edge traceability based on the relationships between knowledge elements and key factors, lack of procedural knowledge to provide adequate policies to guide changes, and lack of ‘lessons learned’ documentation in knowledge bases. A qualitative method was used to investigate issues surrounding knowledge mobilisation and knowledge networks. Empirical study was undertaken with industries to test the CMKNM. Results are presented from the empirical study on the key factors influ- encing knowledge mobilisation in IT project-oriented change management, knowl- edge networks and connections. The CMKNM model allows key knowledge mobilisation factors to be aligned with each other; it also defines the connections between knowledge networks allowing knowledge to be mobilised by tracing knowledge channels to support decision.

Keywords: knowledge networks; knowledge mobilisation; strategic decision-making; project-oriented change management; organisational change knowledge and IT projects

1. Introduction

Knowledge management and change management concepts are widely described in the literature as being interwoven (Bloodgood & Salisbury, 2001). They are multidisciplin- ary fields which seek to enhance the utilisation of organisational assets for competitive advantage (Birasnav, Rangenekar, & Dalpati, 2011; Wiig, 2000). However, many organisations usually consider knowledge management as a complementary concept, subsequently failing to address its value within change management strategies to sup- port effective decision-making throughout all processes and phases of change. In fact, not only knowledge is a prerequisite to the ability to influence outcomes; knowledge motives for change also assist in lessening uncertainty and generating readiness for change (Terry & Jimmieson, 1999). Knowledge management can provide the key power in influencing change at various levels, including the processing of change, designing the change project, spearheading organisational readiness, supporting decision-making processes, dealing with cultural issues and eventually enhancing the

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© 2014 Taylor & Francis

Journal of Decision Systems, 2014 Vol. 23, No. 3, 285–302,

success of change (Van Donk & Riezebos, 2005). This is because knowledge management is able to facilitate a variety of organisational functionalities including work performance, decision-making, social cognition and strategic management (Van Donk & Riezebos, 2005). Some scholars believe that the key competencies of organisa- tions are built upon employees’ experiences and skills, thus highlighting the need to find ways of tapping into such knowledge to develop and maintain core capabilities (Gareis & Hueman, 2000). Therefore, one of the most critical failure factors related to inadequate decision-making systems is a result of the poor selection of change manage- ment strategies; this can be attributed to a lack of knowledge and poor knowledge man- agement (Bloodgood & Salisbury, 2001; Burnes, 2004). Knowledge management and change management strategies always call for new approaches to supporting decision- making in order to deal with ongoing organisational issues (Cao & McHugh, 2005).

Most of the existing change management work discusses the specific characteristics of project-oriented companies and their transformation (Keegan, Huemann, & Turner, 2012; Rebecca, 2013); change models and approaches, the relation between change processes, projects and programmes (Gareis, 2010); and the role of human resources. A small amount of the work makes brief statements about knowledge management and the role of project managers as a strategic core resource in project-oriented companies (Huemann, Keegan, & Turner, 2007; Keegan et al, 2012). Three epistemological knowledge management perspectives were identified in project-oriented organisations: (1) examining the interaction between tacit and explicit knowledge for managerial prac- tices (Christensen & Bang, 2003), (2) identifying and examining factors that influence the success or failure of knowledge management initiatives in project-based companies (Ajmal, Helo, & Kekäle, 2010) and (3) examining the key problems in embedding new management knowledge within processes of change (Bresnen, Goussevskaia, & Swan, 2004). Most research in project-based change management has been conducted in Eur- ope, so there is a need to conduct research in different parts of the world in order to offer new insights and to strengthen existing findings.

Additionally, most of the existing work considers organisational learning as a type of change with two processes: acquiring new knowledge and stabilising new knowl- edge. The phases in each process have their own supporting tools and mechanisms. Furthermore, organisational learning can undergo continuous improvement through daily business activities to promote innovation in an organisation (Gareis, 2010). More work is needed on employing a systematic approach to project-oriented change man- agement that is driven by applying knowledge management, which could accompany the existing change management strategy to support better decision-making processes. Little research exists on the use of knowledge management in project-oriented organisa- tions which considers the creation, sharing and application of knowledge in relation to optimising performance in project management (Love, Fong, & Irani, 2005). However, such work does not view projects as permanent organisations nor does it consider issues regarding decision-making support mechanisms.

To address the previously relatively unexplored and undeveloped issues, this paper aims to contribute to the development of an understanding of knowledge management mobilisation and knowledge networks by proposing a change management knowledge network model (CMKNM) in order to provide traceability and the connection of proce- dural knowledge to ‘lessons learned’, to ultimately enhance decision support for strate- gic intervention in information technology (IT) project-oriented change management. In particular, this paper focuses on:

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� Establishing a new ‘practical’ insight into knowledge management mobilisation in supporting decision making.

� Identifying a new knowledge layer of ‘know who’ in addition to the already existing layers of ‘know how’, ‘know what’, ‘know why’ and ‘know with’.

� Identifying the key knowledge mobilisation issues in IT project change that have an impact on decision support, as well as determining key knowledge mobilisa- tion factors in project-oriented change management for structural knowledge net- works.

The paper is organised as follows. The following section reviews relevant literature, while Section 3 proposes a conceptual framework for knowledge mobilisation in change management. Section 4 discusses the research methodology to evaluate the con- ceptual model, followed by Section 5 on empirical results. Section 6 concludes the study and suggests future work.

2. Literature review

This section reviews related work addressing knowledge mobilisation to support deci- sion-making in IT project-oriented change management. This review particularly focuses on knowledge mobilisation networks, and how they are used in supporting decision-making in project oriented change management.

Interests in knowledge mobilisation have grown rapidly over the last decade. Scholars from different disciplines have had different views on knowledge mobilisation. So far, there has not been a single definition that can be agreed on by all scholars. The main rea- sons for this diversity may result from a lack of consensus concerning knowledge man- agement terminology; a lack of agreement regarding knowledge management issues, resulting in variety of conceptual frameworks, and because knowledge management itself is multidisciplinary, stretching across a range of academic fields and sectors. The three main perspectives on knowledge mobilisation are developed from education, health and business. The education perspective takes an epistemological standpoint towards the role of knowledge mobilisation in supporting education (Levin, 2008). Knowledge mobilisa- tion is viewed as comprising the transfer, dissemination and translation of knowledge (Cooper, Levin, & Campbell, 2009). Knowledge mobilisation is further defined as influ- encing decision-making by transferring the right information to the right people by the right means at the right time (Levin, 2008). There is still some ambiguity in this defini- tion. It assumes that knowledge mobilisation concerns ‘transfer’, ‘disseminate’ and even ‘translate’, all of which are related to knowledge sharing in knowledge management liter- ature (Gould & Powell, 2004; Huang, Newell, Pan, & Poulson, 2001). This illustrates the overlapping concepts in the literature that cause confusion regarding knowledge manage- ment. A second view is from the health sector which refers to knowledge translation as a continual dynamic process consisting of the synthesis, diffusion and exchange of knowl- edge to create effective healthcare systems (Gagnon, 2011). A third view builds upon the role of knowledge brokering from a business perspective but is more concerned with innovation in a corporate business environment rather than on understanding the concept of knowledge mobilisation (Cooper, 2012).

On the contrary, there has been some consistency in the literature on the importance of knowledge mobilisation in support of decision-making. Three definitions are offered here in order to discuss issues surrounding knowledge mobilisation, along with their

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relation to decision support. The first is that of Levesque (2013), who view knowledge mobilisation as a complex process encompassing collective knowledge, ideas and con- cepts used to take action to meet certain objectives. This definition, though sounding generic, highlights some important elements in knowledge mobilisation which support decision-making: for instance, the knowledge-gathering process regarding a specific issue as an input, the process of analysing and making decisions, and finally the evalu- ation of outputs. The second definition concerns how knowledge mobilisation addresses knowledge outside the organisation, combining this with the knowledge already exist- ing inside the organisation to create and then utilise new knowledge (Creech, 2004). This highlights the connections among organisations, stakeholders, people, systems, etc. The third view indirectly offers the term ‘knowledge mobilisation’ from the connection of people, the organisation, resources, culture and the community of practice (Jashapara, 2011). This appears to avoid giving a clear definition of knowledge mobilisation. However, the author seemingly classified knowledge mobilisation as an organisation’s network of intellectual assets.

From examining previous studies, the knowledge mobilisation literature implicitly highlights terms such as networks (Jashapara, 2011), connections (Creech, 2004), actions (Levesque, 2013), linkages (Levin, 2008), brokering and intermediaries (Cooper, 2010) as existing between contents, contexts, systems and groups. These are driving forces when attempting to achieve comprehensive insights into the meaning of knowledge mobilisation. In this light, some of the logical factors and issues included in knowledge mobilisation activities have been identified. For instance, Jashapra (2011) pointed out a variety of aspects involved in knowledge mobilisation or knowledge networks, including the differences between organisational culture and organisational climate, issues regarding building communities of practice, embedding knowledge man- agement technology to achieve a desired culture, cultural typologies and their impact on knowledge sharing (techniques and strategies), the role of management in cultivating a community of practice, concerns with regard to intellectual capital, knowledge man- agement strategies based on culture and communities of practice, and implementing certain aspects of knowledge management into change processes. Likewise, Hislop, Newell, Scarbrough, & Swan (2000) suggested certain factors that influence change in knowledge networks, focussing on, for example, the type of structure and the power of authority and political involvement in supporting decision-making. Keen (1981) based the fundamental concept of networking within the notion of leading change where many issues must be considered. These issues include knowledge and experience, les- sons learnt, authority and political involvement, change champions (teams, leaders, change agents and management), processes and structure, resistance to change and its cultural, technological, political and structural issues, and the size and scope of any change. These may be highly associated with tacit knowledge (or ‘know how’) since, as Hislop et al. (2000) point out, ‘know how’ and networks are inextricably interre- lated. However, Carud (1997) put forward a clear distinction between ‘know how’, ‘know why’ and ‘know what’. The term ‘know how’ deals with only one component of intellectual capital in knowledge management, although it is widely used. ‘Know why’, however, represents an insight into the roots of issues and reasons why some things could happen (wisdom level) whilst ‘know what’ represents ‘an appreciation of the kind of phenomena worth pursuing’ (p. 81). Taking this into consideration, two case studies conducted by Hislop et al. (2000) are of interest in introducing enterprise resource planning (ERP) and information management (IM) systems. They highlighted the problems that could occur when key knowledge holders were not involved in

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decision-making processes. The failures, in both cases, pinpointed concerns regarding the relationships and connections in a sophisticated culture when political considerations were involved. This may point attention to ‘know who’ in knowledge mobilisation which plays the central role in connecting different parties and resources together. Additionally, this reinforces the work of Jashapara (2011), based on Handy (1985), who outlined four types of organisational culture (power culture, role culture, task culture and personal culture) with particular characteristics and distinctive function- alities. Findings regarding these types suggest their impact on networks or mobilisation. Thus, understanding an organisation’s culture is a basis for decision-makers to suggest knowledge mobilisation strategies as well as other factors which might be involved (Gould & Powell, 2004).

Despite the importance of knowledge mobilisation in knowledge management activi- ties, there is a lack of practical research in this area, so clear evidence concerning issues surrounding it is weak. From 81 papers on knowledge transfer and exchange in health, Mitton, Adair, McKenzie, Patten, and Perry (2007) found that only 18 were conducted empirically while the rest demonstrated certain barriers and constraints. Levin (2008) claims that knowledge mobilisation research still lacks evidence while the literature of knowledge management lacks evidence of a practical nature; many studies have been built on a separate framework rather than building on previous work to offer new insight into knowledge mobilisation issues. Thus, while some research has been conducted in the area of knowledge mobilisation, most of it focuses on enhancing the education or health sectors in only one part of the world. Organisational issues regarding knowledge mobili- sation have been relatively unexplored, although Gould and Powell (2004) attempted to understand the nature of organisational knowledge in supporting decision-making sys- tems. Useful work on knowledge mobilisation and decision-making was carried out by Lavis, Robertson, Woodside, McLeod, and Abelson (2003) who surveyed 265 directors in health and economic/social sectors. This study found a strong relationship between research organisations that targeted more samples across different industries and profes- sions, with knowledge management (KM) scholars understanding best how such activities should be undertaken in this regard. Lavis et al. (2003) argue that having a more targeted audience increases commitment to knowledge mobilisation and so more resources are made available. Additionally, many knowledge management strategies will be applied according to their consistency with the evidentiary base, increasing the likelihood of knowledge management being understood among organisations with multiple target audi- ences. The framework of this study focuses on three key elements: the type of message transferred by mediators, targeted people, and tools and process supporting knowledge management. This framework also highlights the important role played by knowledge networks, particularly in decision-making and knowledge mobilisation processes.

Based on the above, there has been a clear gap in the literature in addressing the knowledge mobilisation networks for decision support with sufficient empirical evidence. This paper aims to fill the gap in literature. The following section presents a conceptual model first followed by empirical study in Sections 4 and 5.

3. A conceptual framework for decision support – CMKNM

Given the lack of literature surrounding knowledge mobilisation networks, particularly in IT project-oriented change management, four interrelated problems, identified in the literature regarding decision support from a knowledge management and change management context, set the stage for this study:

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� A lack of top management support in identifying knowledge management channels in change management processes to support decision-making (Gareis, 2010).

� A lack of project documentation and a lack of procedural knowledge in change management regarding lessons learnt (Ajmal et al., 2010; Gareis, 2010; Gould & Powell, 2004; Smith, Burstein, & Sowunmi, 1999).

� A lack of coordination of collective knowledge, enhanced in decision support systems (DSS), among parties (Garcia-Lorenzo, 2008).

� A lack of employees’ involvement in knowledge mobilisation and change management processes in terms of planning, decision-making and creating a vision (Ajmal et al., 2010; Hossain & Shakir, 2001; Rebecca, 2013).

A conceptual framework is built upon previous research, integrating change management and knowledge management approaches, drawing, for example, from a number of reviews of factors that influence KM in organisations (Ajmal et al., 2010; Ward, House, & Hamer, 2009a). The conceptual framework is named CMKNM. In project-based change in an IT intervention, most identity dimensions of an organisation have to be considered, including strategies, structures, policies, cultures, decision pro- cesses, patterns and connections, and the relevant external environment (Gareis, 2010). The alignment between information technology and business visions, objectives, demands and strategy is key in influencing decision-making processes to determine the capacity for change of an organisation when pre-selecting an appropriate change strategy, and at the implementation and post-implementation stages (Lutz, Boucher, & Roustant, 2013). This CMKNM framework addresses the alignment between key factors of project-oriented change management and knowledge mobilisation to achieve a long-term strategic vision which includes the organisation’s culture and strategy, its capacity and its knowledge infrastructure, as shown in Figure 1.

Figure 1. The change management knowledge networks (CMKNM) conceptual framework. Notes: IT, information technology; KM, knowledge management.

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Knowledge infrastructure is integrated into change management strategies to facilitate knowledge mobilisation; this is important in establishing knowledge networks and in providing traceability and the connection of procedural knowledge to ‘lessons learned’, resulting in the ability to support decision-making. However, to address fac- tors such as interoperability, coordination, cooperation and regulations to support deci- sion making, a few knowledge mobilisation studies have highlighted the role of knowledge brokering and knowledge intermediaries in educational sectors (CHSRF, 2003; Cooper, 2010; Hossain & Shakir, 2001; Ward, House, & Hamer, 2009b). In line with the aims of this study, the role of knowledge brokering is adopted into the knowl- edge network processes in order to understand the full scope of the efforts required in DS processes to ensure the success of IT projects. In the business sector, knowledge brokers are considered to be key players in innovation processes, acting as facilitators, enhancing the combination of knowledge and skills needed in problem-solving innova- tion, and acting as a channel or bridge in connecting suppliers with seekers (Cooper, 2010; Hossain & Shakir, 2001; Sousa, 2008). Knowledge brokers might be an organi- sation, individuals, third parties or change agents who facilitate collaboration and inno- vation by connecting different organisational activities both internally and externally (Cillo, 2005). This is relevant since IT intervention project-based change management consists mostly of outsourcing, especially in large implementation projects. The CMKNM model suggests that knowledge transfer is a dynamic process centred around the classic socialisation, externalisation, combination and internalisation (SECI) model proposed by Nonaka & Takeuchi (1995). This is because of the increasing complexity of the business environment, as well as the dynamic nature of organisational change. Thus, CMKNM defines knowledge mobilisation as a dynamic process of continuous knowledge transfer, consisting of knowledge networks to connect knowledge brokering, knowledge bases, effective knowledge and knowledge seekers while aligning key organisational factors to support decision-making. Investigating issues regarding knowl- edge mobilisation for decision support is particularly important when organisations are going through the further developing or transforming types of changes which result in changes in structure, culture, strategies and functionalities. Such change needs an appropriate mechanism to enhance the sharing, acquisition and documentation of knowledge. Key factors that affect knowledge mobilisation include organisational cul- ture (Jashapara, 2011), organisational strategy (Kezar, 2001), organisational capacity (Stulgienė & Čiutienė, 2012) and knowledge infrastructure, while knowledge mobilisa- tion is enabled by establishing knowledge networks (Manning & Sydow, 2011). In order to align key knowledge mobilisation organisational factors, it is important to define connections between four types of knowledge networks: these are the knowledge networks of interaction, of interpretation and translation, of influence, and institutional knowledge networks (i.e. the knowledge base). Defining the connections between knowledge networks potentially provides knowledge traceability and thus creating decision gates to align key knowledge mobilisation organisational factors.

Issues concerning decision-making processes are a focus for many change manage- ment scholars (Garcia-Lorenzo, 2008; Gareis, 2010) and change management theory offers a variety of models and strategies to manage change. One of the foremost theo- ries which has strongly influenced academics and practitioners is Lewin’s Planned Change Theory (1947). It consists of the following three stages: unfreezing the current state, taking action, and refreezing from the past state. Several models ha