Knowledge sharing assessment: An Ant Colony System based Data Envelopment Analysis approach Chuen Tse Kuah a , Kuan Yew Wong a,⇑ , Manoj Kumar Tiwari b a Department of Manufacturing and Industrial Engineering, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 UTM Skudai, Malaysia b Department of Industrial Engineering and Management, Indian Institute of Technology, 721302 Kharagpur, India article info Keywords: Knowledge sharing Performance evaluation Data Envelopment Analysis (DEA) Monte Carlo simulation Ant Colony System (ACS) abstract Knowledge sharing as one of the most crucial processes in knowledge management, operates in a dynamic environment. Dedicated tools to measure its performance under such an environment are not found in the literature. This paper aims to fill this void by proposing a hybrid model based on Data Envel- opment Analysis (DEA). Monte Carlo simulation is incorporated into the model to handle stochastic data. In addition, to improve the model’s accuracy, the Ant Colony System (ACS) metaheuristic is blended with Monte Carlo simulation and DEA. The model is named ACS-DEA and is found to be able to increase the accuracy and reliability of the results. Although this model aims to assess knowledge sharing perfor- mance, it could also be used in other relevant fields in dynamic settings. Ó 2012 Elsevier Ltd. All rights reserved. 1. Introduction In this rapidly changing world, knowledge has become the most powerful leverage for an organization to achieve competitive advantages. It is therefore crucial for an organization to effectively manage its knowledge. Knowledge Management (KM) can be bro- ken down into a few sub-processes such as knowledge creation, knowledge storing, knowledge sharing, and knowledge utilization. Indeed, all these processes play important roles in forming a successful KM program. Particularly, knowledge sharing is well-recognized as the main element for KM to thrive. For many organizations, getting workers to share and contribute knowledge is the emphasis of their KM initiatives. However, as revealed by past research, most existing frameworks and assessment tools broadly cover the area of KM, and only few are targeted specifically at knowledge sharing (Liebowitz & Chen, 2003; Small & Sage, 2006). Effectively managing and evaluating knowledge sharing performance have emerged to become a critical research subject (Liu & Tsai, 2008). Through performance assessment, organizations could measure how well they are performing in knowledge sharing and then determine the appropriate improvement strategies and resource allocations for their projects. Recognizing the needs, this paper proposes the use of Data Envelopment Analysis (DEA), integrated with Ant Colony System (ACS) and Monte Carlo simulation, to devise a knowledge sharing assessment model. DEA, proposed by Charnes, Cooper, and Rhodes (1978) is a methodology to measure the efficiencies of a group of homogenous organizations without involving much subjective judgments. Since knowledge sharing is stochastic in nature, Monte Carlo simulation is utilized to introduce stochasticity into the DEA model. ACS is used to further enhance the accuracy of the model. Following this introduction, a review on knowledge sharing and existing evaluation models will be presented. Next, the developed knowledge sharing assessment model will be explained. Then, to demonstrate the applicability of the model, a real world applica- tion will be presented. Finally, the paper concludes by giving a summary of the work and some future research directions. 2. Literature review 2.1. Knowledge sharing Knowledge sharing refers to the exchange and transfer of knowledge among individuals, groups, and organizations for the purpose of improving organizational competitiveness by the effec- tive exchange, integration, and synergy of knowledge (Lee, 2001; Chen, 2008; Lawson, Petersen, Cousins, & Handfield, 2009). It can also be viewed as a combination of interaction, communication, and learning processes that allows people to acquire knowledge from others. It fosters a learning environment and permits the cre- ation and recycling of specialized knowledge (Dyer & Nobeoka, 2000). Knowledge sharing contributes towards organizational creativ- ity. Paul, William, Abraham, and Xiao (2004) suggested that new product development is strongly correlated with knowledge shar- ing. In addition, Law and Ngai (2008) revealed that knowledge 0957-4174/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.eswa.2012.12.027 ⇑ Corresponding author. Tel.: +60 7 5534691; fax: +60 7 5566159. E-mail addresses: wongky@mail.fkm.utm.my, kuanyewwong@yahoo.com (K.Y. Wong). Expert Systems with Applications 40 (2013) 3137–3144 Contents lists available at SciVerse ScienceDirect Expert Systems with Applications journal homepage: www.elsevier.com/locate/eswa