Social media has evolved at a rapid pace, influencing every aspect of the global community. The purpose of this paper is to use bibliometric analysis tools to evaluate valid works on the relationship between social media and information sharing. A review study of research papers on social media and information sharing published between 2009 and 2020 was conducted. The bibliometric analysis identified the following characteristics: (1) the primary articles are based on information sharing through social media; (2) the main authors deal with information sharing in social media; (3) the newestrend topics related to information sharing in social media are demographic characteristics, cognition, sentiment, healthcare, products and services recommendations, tourist recommendations, and COVID-19. The results show significant impact rates in studies of information sharing in social media. Overall, this study serves as a basis for new scientific questions that will contribute to the further development of this research field.

Purpose: The current study aims at developing a conceptual framework containing original dimensions of SERVQUAL and adding two modified dimensions: patient safety and medical professionalism in healthcare service quality (HSQ) model.Design/methodology/approach: An extensive review of HSQ literature pertaining to its dimensions and models with respect to content analysis and bibliometric studies of service quality in healthcare and SERVQUAL in healthcare were performed on 47 relevant studies, 4,689 and 529 documents after applying inclusion and exclusion criteria. Google Scholar and Scopus were the primary sources to find the relevant documents.Findings: The content analysis was conducted to group HSQ dimensions into seven themes. Co-occurrence analysis of author keywords was performed in VOSviewer to find the links between service quality, SERVQUAL and proposed dimensions. Organization and analysis of different HSQ models and dimensions emerged from the literature result in a comprehensive conceptual framework comprising modified dimensions of healthcare service quality – medical professionalism and patient safety.Originality/value: SERVQUAL is a widely accepted, tested and validated model in perceiving HSQ from the lenses of patients. But it does not cover the complex nature of healthcare service, thus requiring modification and the addition of new contextual dimensions. Therefore, a comprehensive conceptual framework is developed to validate and test quantitatively.

Understanding the relationships among CO₂ emissions, energy consumption, and economic growth helps nations to develop energy sources and formulate energy policies in order to enhance sustainable development. The present research is aimed at developing a novel efficient model for analyzing the relationships amongst the three aforementioned indicators in G20 countries using an adaptive neuro-fuzzy inference system (ANFIS) model in the period from 1962 to 2016. In this regard, the ANFIS model has been used with prediction models using real data to predict CO₂ emissions based on two important input indicators, energy consumption and economic growth. This study made use of the fuzzy rules through ANFIS to generalize the relationships of the input and output indicators in order to make a prediction of CO₂ emissions. The experimental findings on a real-world dataset of World Development Indicators (WDI) revealed that the proposed model efficiently predicted the CO₂ emissions based on energy consumption and economic growth. The direction of the interrelationship is highly important from the economic and energy policy-making perspectives for this international forum, as G20 countries are primarily focused on the governance of the global economy.

Purpose: This research is an effort to conceptualize the relationship between total quality management (TQM) and knowledge management in a new way. While some researchers considered knowledge management as a facilitator of TQM other scholars concerned TQM as an antecedent for knowledge management. The purpose of this paper is to propose a reciprocal causation between TQM and knowledge management. Design/methodology/approach: The main focus of literature review is focusing on common practices of TQM and knowledge management. In the next step, joint variance analysis method is used to reanalyze the results of the empirical studies linking TQM to knowledge management. This approach aims to divide the multiple correlation squared and demonstrate what portion is distinctly connected to predictor variables and what portion is on account of common variance among predictors. Findings: The result indicates that nearly half of all explained variances in empirical studies that considered the relationship between TQM and knowledge management disregarding the criteria are accounted for the joint variance of TQM and knowledge management processes. Therefore a reciprocal causation between TQM and knowledge management can be formulated. Originality/value: This research is one of the first studies which explores the diverse results of the relationship between TQM and knowledge management from a methodological perspective.