KNOWLEDGE WASTE IN ORGANIZATIONS : A REVIEW OF PREVIOUS STUDIES

ABEPRO DOI: 10.14488/BJOPM.2015.v12.n1.a15 In this paper, we are interested in the knowledge that is “wasted” in organizations, that is existing relevant knowledge that is overlooked in the process of knowledge conversion. Given the competitive pressure firms are facing in today ́s business environment, a waste of knowledge is not only costly but also dangerous. This means that we consider knowledge from a knowledge at risk perspective. Having this in mind, the purpose of this paper is to review research on knowledge waste in organizations to establish our current body of knowledge regarding this topic. The study consists of a systematic review of 51 peer-reviewed articles addressing knowledge waste in organizations. To the best of the authors’ knowledge, no systematic literature review on this topic has previously been published or presented. The topic seems to be a promising field for intensive research and offers a variety of future research avenues. In view of practitioners, the study ́s finding may enable an increased awareness towards the areas where existing knowledge is at the mercy of “waste”. This can assist practitioners to better cope with risks related to this waste and, therefore, better exploit the (limited) knowledge base available.


INTRODUCTION
Among the different knowledge management activities (e.g.knowledge identification, knowledge creation, knowledge dissemination etc.), it seems that knowledge creation is viewed as more important than the other activities.Markus (2001), however, stresses (she talks about reuse) that the effective reuse of knowledge should take a stronger role, as it is clearly associated with organizational effectiveness.In the same vein, researchers have highlighted the link between the reuse of knowledge and developing competitive advantage (Szulanski, 1996).Consequently, one can assert that a strong consideration of existing knowledge can help firms to improve performance and thus sustain competitive advantage.Based on it, in this paper we will focus on knowledge that is not used.More precisely, we are interested in the knowledge that is "wasted" in organizations, an existing relevant knowledge which is overlooked in the process of knowledge conversion.(Ferenhof, 2011).Given the competitive pressure firms are facing in today´s business environment, a waste of knowledge is not only costly (Bolisani et al., 2013) but also dangerous.As initiatives, which are, after all, repeating already existing knowledge instead of creating new knowledge or recombining it in new ways, it can result in situations in which valuable resources and time are bound and thus not available to other more important business operations.Consequently, this may be damaging not only for the company concerned but also for the economy, as continuously reinventing the wheel blocks from developing.In short, we look at knowledge from a knowledge at risk perspective, i.e. addressing situations in which knowledge that is not used becomes a liability or a risk (Durst, 2012).Against this background, the purpose of this paper is to review the research of knowledge waste in organizations to establish our current body of wisdom regarding this topic.

THEORETICAL BACKGROUND
The relevance of knowledge assets as fundamental strategic factors of successful business that have been widely recognized.(Barney, 1991;Drucker, 1993;Grant, 1991).In fact, more and more organizations attribute their competitiveness to their knowledge assets and specifically their exploitation, and consider knowledge as their distinguishing feature (Nonaka et Takeuchi, 1995).In such an environment, the suitable management of knowledge assets has become a strategic task for company success.
According to Wiig (1993), knowledge management consists of seven activities: creation, sourcing, compilation, transformation, dissemination, application and value realization.In this context many studies have described ways of converting knowledge into value for organizations.One of them is the SECI model proposed by Nonaka et Takeuchi (1997) that involves four main activities: externalization, socialization, combination and internalization.The aim of this model is to extract the tacit knowledge of the people, convert it into explicit knowledge, archive it in the company, make other people learn and internalize it, so that it becomes tacit knowledge again.This proceeding sounds simple in theory, but in practice these processes are not that straightforward.These processes are accompanied by mistakes and disruptions, so instead of taking advantage of the knowledge available the danger is high that it is actually "wasted".
In order to address this challenge, particularly the activities of sourcing, compilation and application, many frameworks and models have been developed that propose the use of ontologies to tackle this issue.For example, Lee et al. (2006) state that ontology in conjunction with Semantic Web Technologies may help to represent and share various types of engineering change-related knowledge in specific contexts.On the other hand, Sherimon et al. (2012) highlight that ontologies have the potential for enabling true knowledge sharing and reusing among heterogeneous agents, both human and computer.Picking up this idea, Zhang et al. (2012), in a design context, suggest the use of ontology for modeling Product Service System (PSS) in order to improve prototyping for knowledge management and knowledge reuse.
Others authors (e.g.Aubry et al., 2011;Buttler et Lukosch, 2013;Komi-Sirviö et al., 2002) applied the idea of lessons learned (LL) to deal with the challenge.LL can be defined as the documented knowledge that is gained from experience for the purpose of improving future performance (Buttler et Lukosch, 2013).Komi-Sirviö et al. (2002) support the creation and maintenance of a LL database as an effective means to store and share knowledge in organizations.Aubry et al. (2011) confirmed that LL-related activities are good means to transfer knowledge.In project-based organizations (PBOs), for example, individuals collect and use LL in order to prevent the "reinvention of the wheel" or repetition of mistakes (Aubry et al., 2011;Buttler et Lukosch, 2013).The reuse of knowledge is applied for knowledge sourcing, compilation and dissemination and focuses on the ability to locate and use previously generated knowledge (Watson et Hewett, 2006;Wee et Chua, 2013;Zhang et al., 2013).
Thus, different actions have been developed to manage knowledge in a better way, but those actions could be improved (i.e.being more effective) if one would take into consideration the waste of knowledge that occur during the life cycle of knowledge management (KM) as proposed by Wiig (1993).

KNOWLEDGE WASTE
According to Ferenhof (2011), knowledge waste can be described as any failure in the process of knowledge conversion, better known as spiral of knowledge creation of Nonaka et Takeuchi (1997).Thereby, Ferenhof proposes that the waste can present itself in different ways: reinvention, lack of system discipline, underutilized people, scatter, hand-off, wishful thinking.
Reinvention is a type of waste that happens if the organization does not take advantage of the designed solutions, components, projects, experiences or knowledge previously created and/or acquired (Bauch, 2004).After project completion or expiration of maintenance contract, often the knowledge is not internalized, not put in use, or simply forgotten over time.This is likely to lead to efforts that can be equated with "reinventing the wheel" which represent themselves as repeated projects, mistakes or recurring issues (Almarshad et al., 2010).So instead of reusing good practices, and thus supporting innovative practice, and preventing the reinvention of the wheel (Aubry et al., 2011) likely outcomes are wasted activities and reduced project performance (Cheng, 2009;Dani et al., 2006).As effective knowledge transfer is considered as one of the key success factors for company performance (Cheng, 2009), this knowledge reinvention must be avoided or reduced to a minimum.Consequently, if an organization is to succeed in reusing its knowledge assets, resources can be invested in continuous improvements of present and future knowledge stocks, instead of being wasted in efforts of reinvention (Fong, 2005).
Lack of system discipline covers a number of factors related to the clarity of objectives outlined in the organizations.More precisely it covers unclear goals and objectives; unclear rights, roles, responsibilities and rules; poor delivery dates; insufficient willingness to cooperate as well as incompetence or lack of training (Bauch, 2004).
Underutilized people refer to organization members that are not using their skills and expertise in full.Often this is a consequence of missing roles and responsibilities given to them, when in reality, they could assume much more if the process was designed more effectively (Locher, 2008).
Scatter refers to actions that make knowledge become ineffective because of flow disturbances, which is basically the disruption of interaction that is required for collaboration.This category can be divided into two sub-categories: communication barriers and poor tools.Communication barriers directly prevent knowledge flow occurrence.They include: a) physical barriers such as distance, computational incompatible formats, etc.; b) social barriers such as the firm´s hierarchy and management behavior that prevent communication and thus the flow of knowledge, and c) skill barriers that refer to people who are not capable of transforming data into usable knowledge (Ward, 2007).Poor tools, on the other hand, refer to the assumption that tools should support the flow of knowledge and not stifle this flow.As a consequence, the users of these tools may seek to take shortcuts, copy unsuitable operating modes, and therefore cause failures by being forced to use tools that have not been analyzed for their relevance and suitability.By insisting on using these tools, processes end up in a death spiral, i.e. the more one tries to improve the processes the worst the failures (Ward, 2007).Or, to put it another way, the scattered knowledge results in knowledge leakage, and knowledge leakage results in organizational inefficiency (Hu, 2008).
One example of scatter is highlighted by Cheng (2009), who states that knowledge from one project can be separated and scattered in different phases and owned by different participants.This is imaginable in temporary virtual organizations as well as in consulting firms.Those firms normally fail to capture and transfer knowledge that is scattered on those phases and thus increases the likelihood of waste, such as "reinventing the wheel".According to Padova et Scarso (2012), large enterprises also scatter knowledge objects.According to these authors, this is demonstrated by the number of documents the firms continuously create and store.It is difficult to access knowledge that is scattered across different projects, processes, trades, and people (Hu, 2008).In the same vein, Lijuan (2011) highlights that the main objective of KM implementation is to effectively manage knowledge which is scattered throughout business activities or hidden in the minds of staff.
Hand-off occurs when one separates knowledge, responsibility, action and feedback.It results in decisions made by people who do not have enough expertise to make the decision effectively or do not have the opportunity to accomplish it.Useless information and waits can be specified as subcategories (Ward, 2007).According to Ward (2007), information is useless when it does not help in understanding the customers, because the information does not add value to flow, innovation, and improved decision-making.Instead it would actually be created to fulfill someone's own interests.Waits, on the other hand, normally occurs through the establishment of standard conventional sequencing of activities, which creates a batch processing and causes slow processes.A single path to follow, instead of multiple streams or paths of information and a large variation of work in the batch cause the waste of scatter (Ward, 2007).
Wishful thinking means to follow the subject's own reasoning, based on interests, wishes rather than on facts or rationality, or decision-making is based on one's own perception of reality respectively.For Ward (2007), this means operating in the dark, blindly making decisions without consistent and backing data.This aspect can be divided into specification test and discarded knowledge.Specification test is a practical conventional pattern.This means it cannot be assessed whether a good or service is ready for commercialization, i.e. it is statistically impossible to execute enough tests to be confident that there are zero defects (Ward, 2007).On the other hand, discarded knowledge happens for a number of reasons.For example, teams and superior focus on the product or service launch, thereby leaving aside the capture of knowledge.While the specification tests used do not provide enough information to be used in forthcoming projects and, to make it even more complex, just a few people know how to turn the data available into usable knowledge (Ward, 2007).
In conclusion, the authors of this paper believe that the (negative) consequences of knowledge waste are high.The organization is in a continued reinvention process and loses valuable financial and non-financial resources.For example, the waste of knowledge may reduce the time resources available to innovation, thus challenging firm´ competitiveness (Baxter et al., 2008).Another consequence could be that the firm fails to offer high quality solutions (Demian et Fruchter, 2009).Additionally, any investments in KM activities would be very difficult to justify, as one of the main reasons for disappointment regarding these investments is assigned to missing knowledge reuse (Liu et al., 2013).Given the role of knowledge as the most important strategic factor for firms (Spender 1996) such waste needs to be understood by both the academic and practitioner communities.

METHODOLOGY
In the review process, the authors adopted the principles of a systematic review as recommended by Jesson et al. (2011) namely: Mapping the field through a scoping review, comprehensive search, quality assessment, data extraction, synthesis, and write up.
First, a research plan was developed comprising the research questions of interest, the keywords, and a set of inclusion and exclusion criteria.The paper's onjective was to determine the current status of research on knowledge waste.
We conducted two different researches, the first one focused on understanding the definition of knowledge waste and loss that may occur in companies.The query of this research was "knowledge AND (waste OR discard OR fling OR toss OR "toss out" OR "toss away" OR "chuck out" OR "cast aside" OR "dispose" OR "throw out" OR "cast out" OR "throw away" OR "cast away" OR "put away" OR "missing" OR "squandered" OR "stray" OR "straying" OR lost OR loss OR "knowledge waste" OR "knowledge loss" OR "waste of knowledge".The second query used "knowledge management" AND (reinvention OR "lack of system discipline" OR "underutilized people" OR scatter OR hand-off OR "wishful thinking" OR "knowledge waste" OR "waste of knowledge" OR "knowledge reuse".Additionally, inclusion and exclusion criteria were specified.The inclusion criteria were: peer-reviewed academic papers, English language and the databases Compendex, Scopus and Web of Science.Grey literature such as reports, books and non-academic research; and other languages than English represented exclusion criteria.Moreover, an excel data sheet was produced consisting of key aspects related to the research aim.In the given case these were: name of author(s), year of publication, research aim/objectives, theoretical perspective/ framework, method, main findings, and name of the journal.
Second, once all relevant issues had been specified, two of the authors accessed the databases and looked for suitable articles.The first search had been carried out on June 4, 2013 and resulted in one hundred thirty-nine hits.The second search took place on March 10, 2014 and resulted in three hundred and seventy hits.A third round was conducted on July 1, 2014 which brought about twenty-seven additional hits; resulting in total number of five hundred thirty-six hits.
The third step consisted of two procedures.Firstly, the authors jointly worked through the abstracts to make sure that they actually covered the pre-defined scope.This procedure yielded a final selection of three hundred fifityfive articles.Secondly, the three hundred fifty-five papers were divided among the authors.Subsequently, the authors entered the relevant data regarding the research purpose in the excel sheet.Then, the authors jointly went through each data entry and discussed the content.In the case of possible reservations on the part of the author who had not read the article, the authors went through the article in question.This procedure resulted in a further reduction of the number of papers.In the end, the authors reached a final selection of Fifty-one articles, which fulfilled the criteria, set and thus represented the basis for analysis.This approach helped to alleviate the risk of any inconsistency in the analysis and the conclusion drawn from there.
Fourth, the final excel sheet was jointly discussed involving all authors.This discussion enabled the authors to categorize the findings under themes, which in turn, helped to clarify what is known about knowledge waste and to which areas the body of knowledge is limited.Fifth, the final stage of the review process was devoted to writing up the findings.

PRESENTATION OF FINDINGS
Among the Fifty-one papers that formed the basis for our analysis, the oldest publication is from 1999 and the most recent ones are from 2013.Most papers were published in 2006, 2008, 2011, 2012, and 2013, which suggests that the topic is of emerging interest and relevance.
In the sections below we present our analysis concerning the following aspects: general observations, which outline the research methods applied.After that, the study's main findings according to the themes identified are presented.

General observations
With regard to the methodology, the most common method applied is the case study approach.This is followed by surveys and model approaches.Other methods such as ethnography (e.g.Demian et Fruchter, 2006), mixed methods approaches (e.g.Aubry et al., 2011) are less frequently used.
The Fifty-one papers were published in different journals, which can be assigned to the fields of operations, technology and management; information management; sector studies; general management; entrepreneurship and small business management; and organization studies.This suggests the topic interests a broad audience.
Research in this area has been conducted in different countries and regions and thus seems to be of a global interest as can be seen in Table 1.

Body of knowledge regarding knowledge waste
We summarized the main findings of the investigated studies under seven broad themes: • Application of KM approaches for knowledge reuse

Application of KM approaches for knowledge reuse
Three papers were assigned to this theme (Table 2).The authors report the contribution of knowledge management tools and techniques to knowledge reuse.For example, Ficet-Cauchard et al. (1999) propose a CBR module that makes easier the retrieval of information and knowledge steps.While Garcia-Fornieles et al. (2003) highlight that their integrated WBS approach is able to cope with changing information availability of the different stages of the project life cycle.

Consequences of knowledge loss/waste
Three papers provide insights into the consequences of knowledge loss/waste (Table 3).McQade et al. (2007), for instance, stressed the different types of knowledge that may be lost because of exiting (experienced and expert) employees, i.e. communication skills and understanding of the company culture.

Factors promoting/hampering knowledge reuse
The majority of papers can be assigned to this theme (Table 4).Regarding factors hampering knowledge reuse the studies highlighted the failure to provide learning benefits (Chauhan et Bontis, 2004), novelty of problems, conditions within organizations (e.g.social norms), types of available knowledge, and methods of reusing knowledge (Petter et Randolph, 2009), overall costs involved (Watson et Hewett, 2006).As regards factors supporting knowledge reuse, the contribution of the owner/managing directors as creator and driver of KM activities (Wee et Chua, 2013), willingness of people to contribute valuable knowledge (Watson et Hewett, 2006) were mentioned.The initial results suggest that the community of practice theory presents legitimacy in the study of knowledge management within organizational project management.

ICT solutions
Six papers proposed ICT solutions to better cope with knowledge reuse (Table 5).For example, Allsopp et al. (2002) developed a relational database based on the CommunKads to facilitate knowledge reuse.Baster et al. (2008), proposed a framework to integrate requirements and the design of knowledge reuse.Gu et al. (2011) proposed a method to discover and capture organizational knowledge for reuse.Lee et al. (2006) developed a model to facilitate the accumulation of knowledge for reuse and finally Zhang et al. (2013) proposed a novel method to reuse knowledge.The authors demonstrated the usefulness of risk archetypes and scenario models as suitable means to knowledge retrieval and reuse.

Design of database followed an iterative approach
Demonstrated that CommonKADS knowledge model can be stored in a relational database.
To describe an approach for reusing engineering design knowledge

Literature on design reuse
The methodology is based on a interaction between a product model and a process model.Mainly theoretical/conceptual.Yet, the approach is tested using a case study example The method proposed highlights the need to reuse engineering design knowledge.Mainly theoretical/conceptual.Yet, the approach is tested using a case study example The proposed framework enables the application of requirements management as a dynamic process, including capture, analysis and recording of requirements.
To introduce a Multifaceted and Automatic Knowledge Elicitation System (MAKES) for the purpose of discovery and capture of organizational knowledge N/a Case study in a public organization of Hong Kong Using the MAKES the time, the cost and the workload on taxonomy development and maintenance can be reduced.

2006
Lee et al.
To develop a model and prototype support system for ECM to facilitate the accumulation and reuse of the knowledge generated in collaborative engineering change processes.

Literature on KM Modeling
According to the authors, the proposed model offers the following advantages: 1) it provides a basis for the integration of informal and unstructured off-line collaboration with structured online workflows, 2), the collaboration model demonstrated how Semantic Web technology can help represent and share various types of engineering changerelated knowledge in context.3, in order to store, search, and retrieve engineering cases efficiently, the CBR technique was used along with the concept-based similarity measure.
To propose a novel method to reuse the process knowledge with different manufacturing resources.

Literature on manufacturing KM
Theoretical case study To propose a prototype system that can be used for knowledge capture and reuse Insights into KM practices relating to knowledge reuse Four papers were assigned to this theme (Table 6).The authors of this category discuss the importance of knowledge management practices to reuse knowledge.In example, Dave et Koskela (2009) focused on knowledge creation and transfer process.Demian et Fruchter (2006), also deal with the process but the developed a computer system to deal with this issue.Durst et Wilhelm (2012) highlight the knowledge attrition and examined the risks of it.Fong et Lee (2009), give emphases on the nature of the property of knowledge acquisition, share, transfer and reuse.Hsiao et al. (2006) studied how KM can assist on knowledge reuse.Wee et Chua ( 2013) identified impediments and enablers for knowledge reuse based on the peculiarities of the KM process.The study indicates that knowledge reuse in AEC design practice occurs largely through social knowledge networks.Even when reuse from an external repository occurs, a human expert is usually needed to provide proactive input on what to reuse and contextual information on the designs being reused.These observations are attributed to the effectiveness of internal knowledge reuse, the reuse of knowledge from one's personal experiences.The study also shows the contribution of a corporate memory to design knowledge reuse.

Durst & Wilhelm
To examine how a medium-sized enterprise might identify and manage its critical knowledge.

Literature on KM
Case Study based on a series of semi structured interviews with members of a German medium-sized enterprise active in the printing sector The study's aim was to gain better insights into how a medium-sized company manages its knowledge.The particular interest was to find out how the firm handles knowledge attrition caused by staff turnover or long-term absence of critical staff members.The findings are summarised in a static knowledge map.
To better understand the knowledge reuse process when radical innovation is expected.

Literature on knowledge reuse
Case-Study involved 6 cases of reuse for innovation at Jet Propulsion Laboratory The authors found that reusers in the JPL context balanced the paradox of identifying a non-traditional untested conceptual approach to the problem against the need for risk reduction by picking only those approaches in which they had some confidence.This research shows the extent of knowledge reuse within a period and over time.

Theoretical framework/theory development
Sixteen papers were aimed at developing a theory of reuse and theoretical frameworks respectively (Table 7).Ba et al. (2008) aimed at effectively organizing, integrating, and reusing knowledge.Bennet et Bennet (2008) focused on developing a framework regarding the characteristic of sustainability of knowledge for communities.Berkani et Chikh (2010) proposed a process for knowledge reuse within a community of practice.In their 2013paper, Berkani et Chikh (2013) semantically described the community of practice learning assets.Chai et Nebus (2012) focused on the efficiency of knowledge reuse.Kullkarni et al. (2006) developed a system to share and reuse knowledge based on the perceptions of usefulness and user satisfaction.Lettice et al. (2006) presented a measurement framework to capture the importance of the knowledge for the new product development process.Liu et al. (2013) provided a systematic framework to analyse knowledge reuse.Markus (2001) proposed a theory of knowledge reuse by emphasizing the role of knowledge management systems.Massingham (2008) developed a conceptual model that shows the impact of knowledge loss due to exiting employees.Menolli et al. (2013) proposed social tool to learn and facilitate the knowledge reuse.Petter et Vaishnavi (2008) used the narratives to improve knowledge reuse among software project managers.Sarnikar et Zhao (2008) proposed a pattern-based knowledge framework for automating the knowledge flow at organizations.Tserng et al. (2009) proposed and approach to extract knowledge and develop a project's risk ontology.Wu (2009) presented a methodology to manipulate form-based knowledge.Finally, Zhan et al. (2012) developed an integrated framework for knowledge reuse to product service systems.

Literature on KM and PPS Modeling
The developed knowledge management and reuse system can help Product-Service Systems design for construction machinery.

Other issues
Four papers were assigned to this category (Table 8).Fong and Dettwiler (2009), for example, developed a model that looks into the knowledge creation relationship of entrepreneurial firms and environmental context.The paper shows that real estate decisions are strongly related to the particular environment and conditions that prevail for entrepreneurial firms.The research suggests that knowledge management problems and system adoption difficulties must be understood in relation to knowledge attributes (knowledgeas-object, knowledge-as-cognition, and knowledge-as-capability) and people's practices embedded in their work contexts.

CONCLUSIONS
Against the background of the growing concern of both scholars and practitioners regarding the implementation knowledge management initiatives, the aim of this study was to pay particular attention to the knowledge that is "wasted" in organizations, that exists relevant knowledge that is overlooked in the process of knowledge conversion.Even though many studies have focused on knowledge reuse, they have not highlighted the topic from knowledge at risk perspective meaning situations in which knowledge that is not used becomes a liability or a risk (Durst, 2012).Accordingly, the purpose of this paper was to review research on knowledge waste in organizations to establish our current body of knowledge regarding this topic.To do so we conducted a systematic literature review to identify suitable articles.A final set of fifty-one articles formed the basis for our analysis.
Our review makes clear that the body of knowledge regarding knowledge waste in organizations is still limited.The main findings were categorized into seven broad themes: Application of KM approaches for knowledge reuse, consequences/implications of knowledge loss/waste, factors promoting/hampering knowledge reuse, ICT solution, KM practices relating to knowledge reuse, Theoretical framework/Theory development, and other issues.
The findings suggest that the existing literature provides only fragmented insights into knowledge waste in organizations.Given the importance of knowledge to company, a better understanding of this aspect is very important.Our present study clearly underlines that the topic still calls for more research, which in turn offers scholars a variety of research avenues.
We consider the following future research directions as promising: the development of method to measure knowledge waste in organizations, the expansion of studies on the financial and non-financial impact of knowledge waste on companies, the provision of more empirical work that demonstrate the impact of different approaches and techniques, e.g.lessons learned, ontology on the reduction of knowledge waste in organizations.
The present study is not without limitations.A complete coverage of all the articles considering the issue of knowledge waste could not have been achieved, given the search proceeding chosen.So it may have left out papers that also addressed the topic but used a different language.Yet, it seems reasonable to assume that the review process covered a large proportion of the studies available.Finally, this paper proposes some research directions, which are not exhaustive but represent initial stages.

•
Consequences/implications of knowledge loss/waste • Factors promoting/hampering knowledge reuse • ICT solution • KM practices relating to knowledge reuse • Theoretical framework/Theory development • Other issues In the following the findings for each theme are presented.Brazilian Journal of Operations & Production Management Volume 12, Número 1, 2015, pp.160-178  DOI: 10.14488/BJOPM.2015.v12.n1.a15 are suppliers and customers, in knowing the company culture and the way things are done and in the loss of maturity and stabilising influence.
Journal of Operations & Production Management Volume 12, Número 1, 2015, pp.160-178 DOI: 10.14488/BJOPM.2015.v12.n1.the influence of a precarious financial situation on activities related to knowledge management and succession planning.Although the organization members are aware of obvious needs for improvement within the firm, their actual scope of action is centered on the execution of current orders.while previous theories of knowledge reuse assumed that integration was done implicitly and/or limited to a few privileged individuals or organizational routines, Wikis help us to reflect on knowledge reuse when such an assumption is no longer warranted.Wikis make integrative behaviors explicit, broadly distributing to the entire community the opportunity to shape.Padova & Scarso To show that a codification, technology-based approach to KM cannot be successfully pursued without taking into due account the cognitive and organizational aspects of the application context.Literature on KM Descriptive and exploratory case study conducted with Ernst & Young Highlight the importance of having convinced people to change their minds and behavior Brazilian Journal of Operations & Production Management Volume 12, Número 1, 2015, pp.160-178 DOI: 10.14488/BJOPM.2015.v12.n1.a15The findings indicated that a lot of "wheel reinventing" of subject material writings can be saved and teaching preparations can be improved by reusing knowledge from past sessions.Although the focus group used for this research, was conducted in one university, it is believed that the findings are applicable to the reuse of knowledge in e-learning environmentsVolume 12, Número 1, 2015, pp.160-178  DOI: 10.14488/BJOPM.2015.v12.n1.a15

2006
Hsiao et al.To examine how knowledge management problems and technology adoption difficulties can be analysed through experts' practices embedded in their work contexts Taxonomies of knowledge Case study (processtracing method) involving an Asian office of a leading US-based s e m i c o n d u c t o rf a b r i c a t i o n equipment

Table 1 .
Research on knowledge waste by author, year and first author country 2012 University of Liechtenstein, Vaduz, Principality of Liechtenstein Durst & Wilhelm 2011 University of Liechtenstein, Vaduz, Principality of Liechtenstein Ficet-Cauchard et al. 1999 GREYC-ISMRA, France Fong & Dettwiler 2009 The Hong Kong Polytechnic University, Kowloon, Hong Kong Fong & Lee 2009 The Hong Kong Polytechnic University, Kowloon, Hong Kong Fruchter & Demian 2002 Stanford University, Stanford, California, USA Garcia-Fornieles et al. 2003 Cranfield University, UK Gu et al. 2011 The Hong Kong Polytechnic University, Hong Kong Hsiao et al. 2006 National University of Singapore, Singapore Kulkarni et al. 2006 Arizona State University, USA Kumar 2012 Stockholm University School of Business, Stockholm, Sweden Lee et al. 2006 Massachusetts Institute of Technology, USA Lettice et al. 2006 University of East Anglia, Norwich, UK Lin & Fan 2011 DePaul University, Chicago, USA Liu et al. 2013 National University of Singapore, Singapore.Majchrzak et al. 2004 Marshall School of Business, University of Southern California, USA Majchrzak, A; et al. 2013 University of Southern California, USA Markus 2001 University of Southern California, USA Massingham 2008 University of Wollongong, Australia McQade et al. 2007 University of Limerick, Limerick, Ireland Menolli et al. 2013 Pontifícia Universidade Católica do Paraná, Curitiba, Brazil 2013 Shanghai Institute of Technology, China Zhang et al. 2012 University of Bath, UK

Table 2 .
Literature on the application of KM approaches for knowledge reuse

Table 3 .
Literature on the consequences/implications of knowledge loss/waste

Table 4 .
Literature on factors promoting/hampering knowledge reuse

Table 5 .
Literature on ICT solutions

Table 6 .
Literature on KM practices relating to knowledge reuse

Table 7 .
Literature on theory development/theoretical frameworks

Table 8 .
Literature on other issues related to knowledge reuseThe study takes a first incremental step to building theory on knowledge reuse.It also provides some insights into complementing the use of knowledge repositories with person-to-person social interactions.It highlights the need to recognize that social processes can complement the use of knowledgesharing mechanisms.