The purpose of this research is to investigate the status and the evolution of the scientific studies on the applications of social media in the business. The present research is an applied scientific method based on quantitative approach by using library method and scientometrics indicators. With the use of bibliometric library of R software, scientific products in the field of social media applications in business from 2005 to the end of January 2019, the study overviews trends and achievements of this field. The results show that from the beginning of 2005 through January 2019, 2682 articles have been indexed in Web of Science in the field of social media and business; however, since 2009, scientific productions in this topic have grown rapidly and in 2017, there was a substantial increase in the number of studies. The findings also show that the United States with 1269 published articles and the Business Horizons Magazine with the publication of 73 articles, pioneered in the publications of this topic. Analyzing the content of the works produced in the applications of the social media and businesses can help us better understand the growth trend in this area.

This paper presents an empirical investigation to determine important business intelligence factors influencing on development of export activities. The study selects a sample of business developers who were involved in export activities in city of Tehran, Iran. Cronbach alpha based on standardized items was calculated as 0.882, which is well above the minimum desirable level. In addition, Bartlett & apos; s test of Sphericity yields a Chi-Square value of 3242.82 (df = 861, Sig. = 0.000). Using principle component analysis, the study has determined four factors including competitive position, organizational resources, efficient system and customer orientation influencing on development of export activities.

Having a supply chain is an unavoidable fact and all companies should focus on if they wish to survive in the competitive business world. This paper ranks criteria influencing on behavior of a medicine manufacturer agent when its goal is to select the supplier agents to interact with across a pharmaceutical agent based supply chain. The pharmaceutical industry is important for countries due to the distinguished role of health in societies and Iran is not an exception too. Besides, the industry in this country is encountered with some limitations because of the situation imposed by sanctions. In this study, first, ten criteria were selected based on expert’s opinions, two categories of quantitative as well as qualitative criteria were chosen for ranking the criteria and then TOPSIS and PROMETHEE ? methods were applied to rank the criteria. According to the results of this survey, qualitative criteria were determined as important factors influencing on supplier selection.

In supply chain management, supplier performance is evaluated based on several criteria. In this paper, a fuzzy multi-objective mathematical programming model is presented to consider different qualitative and quantitative factors to choose appropriate suppliers and the optimal order quantity allocated to them. The proposed study uses analytical hierarchy process to rank different suppliers and a fuzzy multi-objective mathematical programming is presented to choose the best suppliers. The study uses NSGAII to solve the resulted problem and the model is analysed using some sample results under various circumstances. The study considers different Pareto solution set obtained by TOPSIS ranking algorithm, and eventually determines the best possible solutions.

The purpose of this research is to provide a conceptual overview on published studies and articles related to social media and information systems as two independent, continuous and interdepend-ent concepts. The research data is from the survey for two social media keywords and information systems from the Scopus site, which is one of the main scientific search engines. Due to a large number of findings, the study area was limited to 6 major areas of social sciences, business management, economics, arts and humanities, psychology and decision-making sciences, and 5185 articles were found. To investigate and analyze the findings, the Romethometrics and bibliometrics library of R Studio software were used. Biblimetrix was a method for studying and evaluating quantitative scientific texts using mathematical and statistical methods. The data obtained from this research is useful for scholars, researchers, decision-makers and those interested in social media and information networks in the political, economic, social and cultural spheres.

Inventory planning for the pre- and post-disaster phases of disaster relief lifecycle is a challenging problem associated with the humanitarian relief supply chains. In this work, two mathematical models are presented encompassing the whole disaster relief lifecycle. By accounting for holding costs of perishable supplies, a two-stage stochastic programming model is first developed by which the inventory prepositioning locations, inventory levels, and short-term distribution quantities are determined. For the recovery phase, this research adapts the well-known continuous review (Q, r) inventory model for relief warehouses while accounting for the inherent epistemic uncertainty in the required data by using the fuzzy programming. A case study of Iranian Red Cross is also provided to illustrate the applicability of the first model and to demonstrate how it supports the two first phases of disaster lifecycle. Additionally, a numerical example is presented to demonstrate the applicability of the (Q, r) model for the recovery phase. Lastly, the impact of penalty costs on the solutions is discussed.

Selection of one or a combination of the most suitable potential providers and outsourcing problem is the most important strategies in logistics and supply chain management. In this paper, selection of an optimal combination of suppliers in inventory and supply chain management are studied and analyzed via multiple attribute decision making approach, data mining and evolutionary optimization algorithms. For supplier selection in supply chain, hierarchical clustering according to the studied indexes first clusters suppliers. Then, according to its cluster, each supplier is evaluated through Grey Relational Analysis. Then the combination of suppliers’ Pareto optimal rank and costs are obtained using Artificial Bee Colony meta-heuristic algorithm. A case study is conducted for a better description of a new algorithm to select a multiple source of suppliers.

The purpose of this research is to investigate the status and the evolution of the scientific studies on the effect of social networks on e-commerce. The study seeks to address the status of a set of scientific productions of researchers in the world indexed in Scopus based on scientometrics indicators. In total, 1926 articles were found and the collected data were analyzed using quantitative and qualitative indicators of scientometrics with bibliometrix R software package. The findings show that researches have grown exponentially since 2009 and the trend has continued at relatively stable rates. Thematic analysis shows that the subject had a significant but not well-developed research field. There is a high rate of cooperation with a rich research network among institutions in United States, European and Asian countries. Studies also show that research interest in this area is prevalent in developed countries. In addition, the lack of funds and complex analytical tools may be due to lack of studies in developing countries, especially in Africa. The study of the global trend of research through scientometrics helps managers and researchers in identifying countries and institutions with the greatest potential for scientific production, which allows them to develop their professions.

Performance measurement plays essential role on improving the performance of business units and their efficiencies. During the past few years, there have been tremendous development in banking systems and the primary focus of many managers is to improve the quality of services for market retention. Performance measurement in banking industry is normally involved with various qualitative as well as quantitative criteria, which leads to the implementation of multiple criteria decision making techniques. This paper presents a hybrid grey relational analysis and K-means to cluster and measure the performance of banking system. The proposed study uses different criteria, clusters banks into various segments and ranks 43 different banks in city of Semnan, Iran.

Mining is one of the most important sectors in most countries. It produces raw material for other sectors such as industry, agriculture, etc. Therefore, governments always seek the solutions to prevent or at least reduce the risk of mining industry to minimize the waste of time and resource. One of the most popular risk in mining industry that should be clearly assessed is supply chain. There is a variety of methods to evaluate and classify risks. Fuzzy set is one of the most appropriate methods to categorize and evaluate risks, because this method is able to take into account the uncertainty involved in the process of risk assessment. In this article, fuzzy inference system is applied to evaluate and assess the supply chain risk of the Iranian mining industry. This research shows that the proposed model had a high accuracy and efficiency for assessing the risk of mining industry.