International Journal of Industrial Engineering & Production Research

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This study proposes an outsourcing mechanism for marketing plans in small and medium-sized enterprises (SMEs) using knowledge sharing.  SMEs may not be able to establish a marketing department due to operational expenditures. Therefore, organizing a marketing agency to handle marketing concerns of SMEs is significant. First, SMEs are clustered regarding their activity area, products, services, and etc. Then, for SMEs in a same cluster, the marketing agency should collect the required information to process marketing actions. The challenge is how to gather and deposit information in common among SMEs in a cluster. Knowledge sharing is one of the stages of knowledge management helping to distribute information among elements of a system. Thus, the process of knowledge sharing is investigated in outsourcing marketing activities. Accordingly, a questionnaire was prepared based on research hypotheses. After confirmation of validity and reliability, the questionnaire was given to managers and employees of furniture companies in Tehran province, Iran. The collected questionnaires were analyzed using SPSS software version 24.0.  According to the statistical sample of the research, descriptive statistics, and inferential statistics were analyzed. Descriptive statistics were used to describe the demographic characteristics of respondents. The inferential statistics, Kolmogorov-Smirnov test was used first for the test of normality of data. Considering normality of the data, T-student test was used to obtain the relationship between variables. Finally, the results of the research showed that there is a positive and significant relationship between outsourcing marketing in SMEs using knowledge sharing. Therefore, it is suggested that SMEs pay particular attention to outsourcing their marketing activities using knowledge sharing.

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One of the challenges that banks are faced with is recognition and differentiation of customers and providing customized services to them. Recognizing valuable customers based on their field of business is one of the key objectives and competitive advantages of banks. To determine guild patterns of the valuable customers based on their transactions and value of each guild for the bank, the banking tools on which the customer’s transactions take place need to be surveyed. Using deeper insights into the value of each guild, banks can provide customized services to ensure satisfaction and loyalty of their customers. Study population was comprised of the holders of point of sale (POS) devices in different guilds and the transactions done through the devices in an 18-months period. Datamining methods were employed on the set of data and the results were analyzed. Data preparation and analysis were done though online analytical processing (OLAP) method and to find guild patterns of the bank customers, value of each customer was determined using recency, frequency, monetary (RFM) method and clustered based on K-means algorithm. Finally, specifications of customers in the most valuable cluster were analyzed based on their guilds and the rules were extracted from the model developed using C5 decision tree algorithm.

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The role of sustainability dimensions in the value creation process has received much attention. Adopting a proper set of key performance indicators sustainability leads to accurate calculation of chain value. This paper focuses on the dimensions of in the biofuel supply chain and seeks to evaluate the value in the chain. First, the importance of biofuels and its various types are discussed. Then, a new model is presented by designing the proposed energy chain and considering its sustainability dimensions and indicators in uncertain environment. Rough set theory is one of the best mathematical tools for dealing with uncertainty. The proposed biofuel energy supply chain is modeled to obtain the total value of the system considering sustainability indicators and layers of the supply chain. A multi-objective rough mathematical formulation is presented and solved. Best-worst method was integrated to determine the significance score of sustainability indicators. Finally, the model of the rough linear mathematical program is solved with optimization tools and the sustainable value of the chain is obtained.

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Providing skills training is an essential need of different societies. Considering the significance of the role of skill training in empowerment and employment of individuals through the training of skilled labor required by the labor market and industry, in this study the supply chain of skills training has been designed. In the proposed supply chain, according to the skill training aspects, a network structure is conceptualized to include appropriate factors in different layers of the supply chain. Evaluating the performance of the supply chain is handled applying a network data envelopment analysis. Network Data Envelopment Analysis (NDEA) is an efficient method analyzing all the factors included in the evaluation network. Among the NDEA models, the output-oriented BCC model was selected due to the importance of the output of the supply chains of the skills training. In addition to efficiency, the concept of complementary loss is also introduced to validate the results. The research findings show the efficiency of various factors in the stages of the designed network. On the other hand, unlike the classic DEA method, which shows the maximum efficiency of a factor, in the proposed network model, the efficiency priority is calculated and the efficiency is determined at each stage of the supply chain.
 

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