Management of Information System

Although cancer research has generally been clinical and/or biological in nature, in recent years, data driven analytic research has become a common complement. In medical domains where data and analytics driven research is successfully applied, new and novel research directions are identified to further advance the clinical and biological studies. Specifically, it is the combination of the serious effects of cancer, the promising results of prior analytical research in related fields, the potential benefits of the expected research outcomes and the desire to further understand the nature of cancer that provided the motivation for this research effort. Therefore, the main objective of this research has been to take advantage of the available data mining tools and techniques to develop accurate prediction models for prostate cancer survivability, and to explain the prioritized importance of the prognostic factors.

Nowadays, there is consensus on the fact that the sustainability, in which the international political debate constitute one of the most powerful concepts, opens entirely new opportunities for reaching higher levels of development. Sustainability development means making sure the social, economic and environmental needs of current generations are met and kept healthy for future generations. Increasing importance of sustainable development

Organisations willing to succeed in global competition have to integrate their internal and external processes. This especially includes planning and production control (PPC) processes. Optimised allocation of the production resources and quick response to demand changes result in lower cost and improvement of production performance. Practitioners and researchers have been trying to achieve these goals using production planning techniques. Although the results are significant, it seems necessary to integrate production operations in order to improve the production performance. The goals, information and decisions taken in production planning and control and process planning are often very different and difficult to integrate in Cellular Manufacturing (CM) environments. Designing an efficient PPC system and integrating it with process planning in a cellular environment is of the same importance. The following paper proposes first a comprehensive framework of integrated process planning and production planning and control in CM. Then, with respect to this framework and utilising the domain knowledge in the area of CM systems, an integrated model based on Integrated Definition Modeling Language is developed. The application of the models has been considered as a case study for a production system in electronics and telecommunication sector in a plant in Iran. The validity and completeness of the proposed model is tested by a panel of experts in the areas of production planning and control in CM environments.

Nowadays, there is consensus on the fact that the sustainability, in which the international political debate constitute one of the most powerful concepts, opens entirely new opportunities for reaching higher levels of development. Sustainability development means making sure the social, economic and environmental needs of current generations are met and kept healthy for future generations. Increasing importance of sustainable development has lead eco-efficiency to find a specific position in literature. Efficiency is an index that measures management ability in optimal use of inputs for generating outputs. A unit can be more efficient if it produces 1) the same outputs with fewer inputs 2) more or better outputs for the same inputs. Data Envelopment Analysis (DEA) is one of the power efficient evaluation methods. In this paper, a new method is proposed for appraising ecoefficiency of manufacturing factories based on an extended DEA approach. The advantage of this model in contrast with current models in eco-efficiency is that DM can keep in perfect control the dispersal of weights. Finally, a case study is implemented by using simulated data in order to evaluate proposed model.

Analytic hierarchy process (AHP) has been considerably criticized for possible rank reversal phenomenon caused by: i, when new alternatives are added or old ones deleted; and ii, when new criteria are added or old ones deleted with the caveat that the priorities of alternatives would be tied under these criteria and hence argued that the criteria should be irrelevant when ranking the alternatives. While in many cases this is a perfectly valid phenomenon, there are also many cases where rank should be preserved. This paper deals with rank reversal due to the inconsistency of the inputs. The preference intensities on REMBRANDT scale are more compatible than AHP scale. The REMBRANDT system is therefore proposed to avoid rank reversal phenomenon. We have provided a practical example to show that the rank reversal phenomenon did not occur with the REMBRANDT system, but did occur with the Wang and Elhag approach.

Inventory record inaccuracy (IRI) is a major obstacle to realizing operational excellence and lean enterprise principles in the supply chain. This paper proposes an analytical model to study the operational and economic impacts of inventory record inaccuracy stemming from theft-type error in a continuousreview lost sale (s, Q) inventory system. The model builds on a Markovian inventory system and finds optimal safety stock and reorder quantity of product by minimizing the expected costs, which are composed of four components: inventory holding cost, production cost, ordering cost, and lost sales cost. This production-inventory model is analyzed across two scenarios depending on which technology is deployed to optimize replenishment decisions: (1) barcode technology and (2) radio frequency identification (RFID) technology. Our numerical analysis illustrates the solution procedure and the effects of the model parameters on the inventory replenishment decisions and total costs.

Online social networks (OSNs) produce a huge volume of content and clickstream data over time as a result of continuous social interactions between users. Because these social interactions are not fully observable, the mining of such social streams is more complex than traditional data streams. Stochastic point processes, as a promising approach, have recently received significant research attention in social network analysis, in attempts to discover latent network structure of online social networks and particularly understand human interactions and behavior within the social networks. The objective of this paper is to provide a tutorial to the point process framework and its implementation in social media analytics. It begins by providing a quick overview of the history of Hawkes point processes as the most widely used classes of point process models. We identify various capabilities and attributes of the Hawkes point processes and build a bridge between the theory and practice of point processes in social network analytics. Then the paper includes a brief description of some current research projects that demonstrate the potential of the proposed framework. We also conclude with a discussion of some research opportunities in online social network and clickstream point process data.

Organisations willing to succeed in global competition have to integrate their internal and external processes. This especially includes planning and production control (PPC) processes. Optimised allocation of the production resources and quick response to demand changes result in lower cost and improvement of production performance. Practitioners and researchers have been trying to achieve these goals using production planning techniques. Although the results are significant, it seems necessary to integrate production operations in order to improve the production performance. The goals, information and decisions taken in production planning and control and process planning are often very different and difficult to integrate in Cellular Manufacturing (CM) environments. Designing an efficient PPC system and integrating it with process planning in a cellular environment is of the same importance. The following paper proposes first a comprehensive framework of integrated process planning and production planning and control in CM. Then, with respect to this framework and utilising the domain knowledge in the area of CM systems, an integrated model based on Integrated Definition Modeling Language is developed. The application of the models has been considered as a case study for a production system in electronics and telecommunication sector in a plant in Iran. The validity and completeness of the proposed model is tested by a panel of experts in the areas of production planning and control in CM environments.

Today's social media platforms are excellent vehicles for businesses to build and foster relationship with customers. Companies create official fan pages on social network websites to provide customers with information about their brands, products, promotions, and more. Customers can become fans of these pages, and like, reply, share or mark the brand post as favorite. Marketing departments are using these activities to crowdsource marketing and increase brand awareness and popularity. Understanding how crowdsourcing oriented marketing and promotion evolves would be helpful in managing such campaigns. In this paper, we adopt a multidimension-al point process methodology to study crowd engagement activities and interactions. Specifically, we investigate the brand post popularity as a joint probability function of time and number of followers. One-dimensional and two-dimensional Hawkes point process models are calibrated to simulate popularity growth patterns of brand post contents on Twitter. Our results suggest that the two-dimensional point process model provides a good model for understanding such crowdsourcing behavior.

Today's social media platforms are excellent vehicles for businesses to build and foster relationship with customers. Companies create official fan pages on social network websites to provide customers with information about their brands, products, promotions, and more. Customers can become fans of these pages, and like, reply, share or mark the brand post as favorite. Marketing departments are using these activities to crowdsource marketing and increase brand awareness and popularity. Understanding how crowdsourcing oriented marketing and promotion evolves would be helpful in managing such campaigns. In this paper, we adopt a multidimensional point process methodology to study crowd engagement activities and interactions. Specifically, we investigate the brand post popularity as a joint probability function of time and number of followers. One-dimensional and two-dimensional Hawkes point process models are calibrated to simulate popularity growth patterns of brand post contents on Twitter. Our results suggest that the two-dimensional point process model provides a good model for understanding such crowdsourcing behavior.

Today's social media platforms are excellent vehicles for businesses to build and foster relationship with customers. Companies create official fan pages on social network websites to provide customers with information about their brands, products, promotions, and more. Customers can become fans of these pages, and like, reply, share or mark the brand post as favorite. Marketing departments are using these activities to crowdsource marketing and increase brand awareness and popularity. Understanding how crowdsourcing oriented marketing and promotion evolves would be helpful in managing such campaigns. In this paper, we adopt a multidimension-al point process methodology to study crowd engagement activities and interactions. Specifically, we investigate the brand post popularity as a joint probability function of time and number of followers. One-dimensional and two-dimensional Hawkes point process models are calibrated to simulate popularity growth patterns of brand post contents on Twitter. Our results suggest that the two-dimensional point process model provides a good model for understanding such crowdsourcing behavior.

Organisations willing to succeed in global competition have to integrate their internal and external processes. This especially includes planning and production control (PPC) processes. Optimised allocation of the production resources and quick response to demand changes result in lower cost and improvement of production performance. Practitioners and researchers have been trying to achieve these goals using production planning techniques. Although the results are significant, it seems necessary to integrate production operations in order to improve the production performance. The goals, information and decisions taken in production planning and control and process planning are often very different and difficult to integrate in Cellular Manufacturing (CM) environments. Designing an efficient PPC system and integrating it with process planning in a cellular environment is of the same importance. The following paper proposes first a comprehensive framework of integrated process planning and production planning and control in CM. Then, with respect to this framework and utilising the domain knowledge in the area of CM systems, an integrated model based on Integrated Definition Modeling Language is developed. The application of the models has been considered as a case study for a production system in electronics and telecommunication sector in a plant in Iran. The validity and completeness of the proposed model is tested by a panel of experts in the areas of production planning and control in CM environments.

Online social networks (OSNs) produce a huge volume of content and clickstream data over time as a result of continuous social interactions between users. Because these social interactions are not fully observable, the mining of such social streams is more complex than traditional data streams. Stochastic point processes, as a promising approach, have recently received significant research attention in social network analysis, in attempts to discover latent network structure of online social networks and particularly understand human interactions and behavior within the social networks. The objective of this paper is to provide a tutorial to the point process framework and its implementation in social media analytics. It begins by providing a quick overview of the history of Hawkes point processes as the most widely used classes of point process models. We identify various capabilities and attributes of the Hawkes point processes and build a bridge between the theory and practice of point processes in social network analytics. Then the paper includes a brief description of some current research projects that demonstrate the potential of the proposed framework. We also conclude with a discussion of some research opportunities in online social network and clickstream point process data.

The age of data analytics requires "data scientists " across a wide range of business disciplines with deep knowledge of how to manage and analyse vast amounts of data to support decision-making. As a result, new analytical tools are being taught in the Management Information Systems (MIS) or business analytics (BA) programs to foster students' development of this critical competency. Three waves of analytics tools are considered from an experiential perspective including how to introduce analytics to first-year business students using an advanced data analytics software package with multiple techniques and data flow interface. SAS Enterprise Miner is used to teach technical topics and perform business-centric data analytics. An innovative exercise is designed in such a way that it guides first-year business students through a learning analytics journey to motivate them to understand the notion of data analytics and to develop skills around this emerging area without delving too much into extraneous technical details. A post-course survey indicated that the exercise helped students understand the opportunities as well as the challenges in doing analytics.

The age of data analytics requires "data scientists " across a wide range of business disciplines with deep knowledge of how to manage and analyse vast amounts of data to support decision-making. As a result, new analytical tools are being taught in the Management Information Systems (MIS) or Business Analytics (BA) programs to foster students' development of this critical competency. Three waves of analytics tools are considered from an experiential perspective including how to introduce analytics to first-year business students using an advanced data analytics software package with multiple techniques and data flow interface. SAS Enterprise Miner is used to teach technical topics and perform business-centric data analytics. An innovative exercise is designed in such a way that it guides first-year business students through a learning analytics journey to motivate them to understand the notion of data analytics and to develop skills around this emerging area without delving too much into extraneous technical details. A post-course survey indicated that the exercise helped students understand the opportunities as well as the challenges in doing analytics.

Organizations recognize the need to adopt Enterprise Resource Planning (ERP) in order to become more competitive, efficient, and productive, although the adoption and implementation of an ERP system is a costly and risky endeavor. Recently, cloud computing has become a viable and competitive means by which most organizations, especially Small and Medium-sized Enterprises (SMEs), can implement an ERP system in a short time frame and cost-effective way. Our research examines the feasibility of cloud-based ERP systems for SMEs through a case study. The case emphasizes the potential of cloud-based ERP systems for SMEs as well as some of the challenges and peculiarities involved in their efforts to obtain an affordable and versatile ERP system. Our findings can potentially guide SMEs to make well-informed decisions throughout their cloud-based ERP adoption process.

Organisations utilise social media technologies for various customer engagement and external facing activities in recent years. This research examines the extent to which the business strategies and social media strategies of organisations are aligned. Using a sample of 33 organisations competing in the information technology industry, the business strategies were operationalised using data extracted from the annual 10-K reports while the social media strategies were identified from the Twitter feeds. Topic modelling with latent semantic analysis revealed six different orientations in the business and social media strategies of organisations, which were used to evaluate alignment. This study also identified clusters of organisations with varying levels of alignment. Implications for research and practice are discussed. ARTICLE HISTORY