Business model analytics: technically review business model research domain

Purpose Although the business model field of study has been a focus of attention for both researchers and practitioners within the past two decades, it still suffers from concern about its identity. Accordingly, this paper aims to clarify the intellectual structure of business model through identifying the research clusters and their sub-clusters, the prominent relations and the dominant research trends. Design/methodology/approach This paper uses some common text mining methods including co-word analysis, burst analysis, timeline analysis and topic modeling to analyze and mine the title, abstract and keywords of 14,081 research documents related to the domain of business model. Findings The results revealed that the business model field of study consists of three main research areas including electronic business model, business model innovation and sustainable business model, each of which has some sub-areas and has been more evident in some particular industries. Additionally, from the time perspective, research issues in the domain of sustainable development are considered as the hot and emerging topics in this field. In addition, the results confirmed that information technology has been one of the most important drivers, influencing the appearance of different study topics in the various periods. Originality/value The contribution of this study is to quantitatively uncover the dominant knowledge structure and prominent research trends in the business model field of study, considering a broad range of scholarly publications and using some promising and reliable text mining techniques

Semantic structures of business analytics research : applying text mining methods

Introduction. Business analytics has grown exponentially over the last decade, combining technologies, systems, practices and applications. It has attracted both practitioners and academics based on its capabilities to analyse critical business data to gain new insights about business operations and the market. The research goal of this paper is to identify major research topics and trends using text mining techniques. Method. We applied text mining methods such as co-word analysis and topic modelling to 1,024 published research documents in the business analytics field found in the Web of Science and Scopus databases. Analysis. We used term co-occurrence maps and latent Dirichlet allocation to mine and visualise data. Results. Findings showed that the knowledge structure of business analytics consists of three main themes: analytical methods, business analytics in practice, and business analytics value creation. Big data analytics, machine learning, and data science techniques are major topics. Further, business analytics research topics were identified and clustered into four thematic groups. Conclusions. The findings present a context for business analytics research development. They show recent trends in the field, namely a predominant interest in big data analytics, social networks, business value, the health sector, and customer retention

Methodological considerations in using the Network Scale up (NSU) for the estimation of risky behaviors of particular age-gender groups: An example in the case of intentional abortion

BackgroundNetwork Scale Up (NSU) is a promising tool for size estimation of sensitive issues. In this study we investigated the important methodological considerations to employ this method for estimating behaviors, such as abortion, which happens in a particular age-gender group.MethodsWe recruited 1250 males and 1250 females aged 18 to 50. Abortion rate was calculated through direct question and NSU methodology. The NSU was applied on three sub-samples (male, female and aggregate). Integrating replies to 25 reference groups, we estimated the network size (C) of respondents and its age-gender structure. To calculate the part of network that is subject to abortion, we compared two approaches: proportional and data based. The Visibility Factor (VF) was calculated through 222 females who had abortion. Direct estimate was considered as gold standard.ResultsUsing C's derived from proportional method, the Relative Bias (RB) in the male and female samples was 33% and 84%. Applying the data-based C's, the RB in the gender-specific and aggregate samples was 5% and 2%.ConclusionThe proportional method overestimates the prevalence. The data-based method to calculate the C is superior. The determination of the age-sex distribution of the network and the specific VF is essential

Evaluation of plasma osmolality using direct method and its measurement in infants under fluid therapy

History and Objectives: Considering the significance of plasma osmolality as an appropriate indicator of water and electrolyte balance, its importance as a stimulus and the extent of its difference with real osmolality, this study was carried out to determine plasma osmolality and its measurement in infants under fluid therapy in selected hospitals in Isfahan.Materials and Methods: The cross-sectional protocol of this study was carried out on 45 infants at an age of 1-10 days in wards of special care for infants. Plasma osmolality was measured using direct method and also through measuring sodium, potassium, glucose and BUN concentrations. Then, paired t-test was applied regarding weight and degree of attention.Results: The measured osmolality was 260.57±1.84 mosmol/kg and was significantly different from the predicted one. These findings were also correct for infants with weights higher than 2500g. Conclusion and Recommendations: The above-mentioned method can correctly measure plasma osmolality as direct method. It is concluded to use in order of importance direct method and then mathematical method for measurement of plasma osmolality

International Journal of Electronic Marketing and Retailing

The world of electronic marketing is continuously evolving. Marketing theories and practices must adapt to these new technological and social scenarios. IJEMR addresses this evolution by analysing new theories and practices as they emerge with particular focus on electronic retailing. Current technological and quantitative approaches to e-marketing, treating consumer relations as a database problem, are insufficient for a deeper understanding of the implications of this evolution. IJEMR fills this gap, fostering new cutting-edge approaches to e-marketing, e-consumers and e-tailing