Seyyed Jalaladdin Hosseini Dehshiri ; Mojtaba Aghaei; Jamshid Salehi Sadaghiani
Abstract
Today, service delivery is changing with the advent of new technologies and the emergence of online businesses. The goal of online businesses and startups is to provide online services while saving customers time and money. One of the startups that are effective in meeting the needs of different groups ...
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Today, service delivery is changing with the advent of new technologies and the emergence of online businesses. The goal of online businesses and startups is to provide online services while saving customers time and money. One of the startups that are effective in meeting the needs of different groups of the community is the Fast Moving Consumer Goods (FMCG). Due to the high consumption rates and spoilage of FMCGs, proper management and performance improvement at different levels of the supply chain is essential. On the other hand, the use of knowledge management is the main factor in the success of the supply chain to achieve a competitive advantage. There are various barriers that lead to failure in the implementation of knowledge management (KM) in the supply chain. Therefore, it is necessary to identify and remove the barriers to the implementation of knowledge management in the supply chain of startups. The purpose of this research is to identify and prioritize strategies for removing barriers to the implementation of KM in FMCG supply chain. The framework in this study is to use the combination of Fuzzy Delphi, SWARA and Gray ARAS. The SWARA method has been used to determine the weight of the barriers, as criteria, and the Gray ARAS method has been used to obtain the final ranking of the approaches to acceptance of knowledge management in the supply chain. Finally, based on the results of this research, the positive leadership towards the adoption of knowledge management in the supply chain was considered as the best way to tackle barriers to the acceptance of knowledge management in the supply chain.
Seyyed Jalaladdin Hosseini Dehshiri; Jalil Heydari Dehooei.Zohrabi
Abstract
Uncertainty is inherent and inevitable component of projects. Research literature suggests that Information Technology (IT)projects and, in particular, outsourcing of these projects are at high risk. Therefore, according to the importance of this field, this study aimed to identify and prioritize ...
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Uncertainty is inherent and inevitable component of projects. Research literature suggests that Information Technology (IT)projects and, in particular, outsourcing of these projects are at high risk. Therefore, according to the importance of this field, this study aimed to identify and prioritize the risks of outsourcing IT projects. Initially, by reviewing the research, a list of identified criteria was provided to the company's experts. Then, the criteria were selected after the scrutiny case study and according to the experts' opinion with the fuzzy Delphi method. In the next step, based on SWARA method, the final weights of the criteria were obtained. Also, after reviewing the literature, a list of important risks for outsourcing IT projects was identified. Then, for the prioritization of the identified risks, ARAS gray method was used. The results showed that the criterion of sharing knowledge and experience as the most important criterion and loss of resources of competitive advantage was identified as the most important risk.
Seyyed Jalaladdin Hosseini Dehshiri; Mojtaba Aghaei; Mohammad’Taghi Taghavifard
Abstract
Recommender systems utilization has proven sales enhancement in most e-commerce platforms. This system objected to provide more options, comfort and flexibility to user which could make him interested, as well as providing better chance for companies to increase sells in their products and services. ...
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Recommender systems utilization has proven sales enhancement in most e-commerce platforms. This system objected to provide more options, comfort and flexibility to user which could make him interested, as well as providing better chance for companies to increase sells in their products and services. Flourishing popularity of web site has originated intrigue for recommendation systems. By penetrating in infinite fields, recommendation systems give deceptive suggestion on services compatible with user precedence. Integrating recommender systems by data management techniques to can targeted such issues and quality of suggestions will be improved considerably. Recent research reveals an idea of utilizing social network data to refine weakness points of traditional recommender system and improve prediction accuracy and efficiency. In this paper we represent views of recommender systems based on Twitter social network data by usage of variety interfaces, content analysis Methods, computational linguistics techniques and MALLET topic modeling algorithm. By deep exploration of objects, methodologies and available data sources, this paper will helps interested people to develop travel recommendation systems and facilitates future research by achieved direction.
