This article provides a systematic review of 191 research articles published on the Information Technology (IT) continuance intention between 2001 and 2014. The IT continuance intention literature was analyzed based on a series of dimensions including year of publication, journal, country, author, research methods, type of respondents, the theories and theoretical constructs utilized, and the contexts and technologies examined. Findings suggest that interest in the topic of IT continuance intention has been increasing steadily in recent years, and becomes an emerging area for academic research into the future. In order to improve research in IT continuance intention, future researchers could apply greater use of the theoretical and methodological approaches such as qualitative methods to investigate the continuance intention of information technology.

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Different studies have considered social commerce as a new paradigm in the field of business and commerce for about a decade and addressed the identification of factors affecting its acceptance. The present study sought to thoroughly review previous research related to the adoption of social commerce. For this purpose, a systematic review of the literature was used with primary and secondary search strategies by utilizing two approaches. First, two hundred sources were reviewed using criteria such as business transactions, social commerce approach, the applied social media, customer engagement cycle, value creation and value co-creation methods, as well as the type of business based on product or service offerings, the innovation space, the employed fundamental theories, and the research method of the studies. Then, the trends and findings from the observed results in the quantitative approach were analysed, followed by distinguishing three generations of social commerce acceptance studies that were conducted over this decade. The results revealed that trust, perceived usefulness, and socialization skills have the greatest impact on social commerce acceptance. Among the various platforms, social networks and microblogs, as well as some e-commerce sites equipped with social constructs were the most used cases in social commerce. The applied theories and models in acceptance studies varied extensively while the technology acceptance model, and the theories related to the planned behaviour, rational action, and social support were frequently used. In addition, different studies focused on user behaviour and the cognitive space of innovation and business-tocustomer transactions, which mainly evaluated the sale of goods through social commerce while the scope of service provision was less prominent. Regarding the research method, most of the studies were non-experimental, descriptive, and survey and the main sources of the dissemination of social commerce acceptance research were journal articles.

As one of three prominent flows (material, money, information) in a supply chain, the information flow plays a key role in supply chain performance and also in reaching high degrees of integrity and cooperation between supply chain members. Regarding the vagueness and multi-dimensional nature of information sharing, evaluating the information sharing level in supply chain is a complex problem. This paper aims to develop a new rule-based inference system to evaluate the level of information sharing in a supply chain. To this end, first, the influencing parameters are obtained from the literature and are screened and refined by the experts, using Lexicography method. Then, they are categorised into a multi-level hierarchical structure. Finally, a hierarchical inference system, which consists of a set of fuzzy rule bases, is constructed to infer the information sharing degree. The use of fuzzy rule bases is due to the lack of explicit functions between the influencing factors as well as ambiguity of these parameters. Also, in this research, the input parameters’ measurement process is defined and some relevant indices are designed. The developed assessment system is a four-leveled hierarchical inference system, built of six fuzzy rule bases. The inference system has eight input parameters, the values of which are calculated utilising six designed indices and two quick questionnaires. Eventually, the developed inference system and the measuring method are implemented in a real case.