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The purpose of this paper is to design a qualitative model of crowdfunding dynamics through the document model building (DMB).

Methodology in this paper is the qualitative system dynamics through DMB. In DMB, the authors identify the variables that are drivers of its growth and collapse, and the model will be developed by using the systematic review of the literature.

Designing of the dynamics of crowdfunding model through DMB. Identifying variables that are drivers of crowdfunding growth and collapse. Determining leverage points in crowdfunding diffusion.

This paper, for the first time, with the aim of identifying and explaining the efficient positive and negative dynamics in this method, examines crowdfunding systematically and structurally.

A large number of systematic reviews (SRs) studies have been performed in the cloud computing field, demonstrating miscellaneous outcomes and utilizing different approaches. Accordingly, a meta-review of cloud SRs is needed to appraise the results of such studies and create an integrated understanding. The paper aims to discuss these issues.

A tertiary study was conducted using a systematic method to analyze SRs including two stages: searching and screening the SRs and thematic synthesis of results. As a qualitative data management tool, Nvivo software was used to support the research process, for data coding and synthesis.

First, by searching electronic sources between the year of 2011–2016, out of a total of 142 identified articles, 94 articles were included according to pre-determined criteria, of which 76 articles were approved after qualitative evaluation. In the second stage, identifying the research themes, a map of the concepts and issues related to each theme was drawn up. The analysis shows that the quality of articles has improved but can be further enhanced using methodological guidelines as well as supporting tools. The research has focused more on the technical aspect, although there is an equal demand for synthesizing of cloud governance concepts.

This is the first tertiary study which presents the main research themes and concepts of cloud SRs in form of thematic maps by using the thematic synthesis and SR methods. This paper also provides some recommendations to improve reviews after evaluating the quality of papers. This study can support reviewers for future SRs in the field and also helps practitioners and managers to have a better understanding of different aspects of cloud computing.

Because of importance of technological learning for less developed countries, the notion has received increasing attention of scholars. The purpose of this paper is to investigate technological learning systematically by assessing the effect of technology transfer actors on technological learning in less developed countries context.

The paper presents assessment model by adopting technological learning concept based on technology absorption and incremental innovation at firm level and identifying key roles of technology transfer actors (State – Scientific and technological infrastructure – Industry) that affect technological learning. The paper follows survey as research methodology. Thus, a questionnaire was addressed to 33 Syrian textile factories to examine the assessment model. Simple linear, multiple linear and ordinal regression analyses are preformed to examine relationships of model components.

The regression models show notable ability of technology transfer actors to explain technological behavior of firms to accumulate operative capability and consequently to generate passive incremental innovation. The findings indicate passive technical change system of Syrian textile industry. Therefore, goal-oriented evaluation of actual technology policy is preliminary step for achieving improvements, as well as activating scientific and technological infrastructure role by enabling strong relationships with industry and supporting interactions of domestic firms of textile industry and with foreign players.

The paper enriches technological learning literature by proposing systematic approach that sets the nature of technical change process of less developed countries in core of analysis. Moreover, it provides a guide for technological learning practices at firm level and for policymakers based on assessing actual status of Syrian textile industry.

Urmia lake water has impressively decreased recently and seriously endangered the lives of the inhabitants. In this paper, the effects of various factors on the reduction of the lake water are investigated and appropriate scenarios are proposed for future improvement. Due to the significant impact of agricultural issues on this crisis, this paper has focused specifically on agriculture. So, this paper aims to forecast and improve the lake water level.

In this paper, a system dynamics (SD) model, which is capable to consider various parameters and variables affecting the lake water level within nonlinear and dynamic relations, is developed.

To show the effectiveness of SD model, real data are used to run the model and the results show that the actual behavior of the lake water is reproduced with high validation (around 98.28 per cent). Also, five different scenarios are proposed to increase lake water volume. The hybrid Scenario 5 (which combines three other scenarios including increasing irrigation efficiency in the agricultural sector, changing cultivation pattern of agricultural products and returning some dams’ water that are consumed in the agricultural sector into the lake) is chosen as the most effective scenario for increasing lake volume about 15 billion m³.

The main contributions of this paper are systemic view to the whole problem, paying attention to the agriculture subject as one of the most important issues, considering many critical variables (e.g. evaporation, salinity and precipitation) and providing improvement policies along with assessing the effects of them.

The principal concern of organization managers in the global rivalry of commerce environment is how to select the project portfolio among available projects. In this matter, organizations should consider the uncertainty intrinsic in the projects regarding an appropriate valuation technique within an optimization framework. In this research, the purpose of this paper is to formulate using a robust optimization algorithm to deal with the complexities and uncertainty inherent in the construction of the project portfolio.

First, a general mathematical formulation is presented, which in compound real options valuation is highlighted. This formulation gives managerial flexibility by correcting the deficiency of traditional discounted cash flow technique that excludes any form of flexibility. Then, considering a limitation on budget of the organization, an integer programming formulation to maximize the n-fold compound options for project portfolio selection is proposed. Finally, a robust optimization model is developed along with the robust combinatorial optimization algorithm, which is effective for solving problems under uncertainty.

Sensitivity analysis showed that projects in later phases of development, having survived several phases of pre-clinical and clinical tests, are worth more because they are more likely to pertain to business. However, the investment costs related to each project during development phases limit the number of projects that a company can bring to their final portfolio. Additionally, the analysis of conservatism level represented how project managers can quite easily determine their risk attitude and the corresponding portfolio composition. From a managerial point of view, the proposed framework is very useful because it requires only financial estimates. Hence, the proposed decision support tool can assist research and development (R&D) project managers in the pharmaceutical industry for making decisions.

The first is the application of the n-fold compound options on portfolio of R&D projects and the employment of compound options value of a project portfolio as an objective function. The second one is a mathematical formulation of these concepts and solving it by the robust combinatorial optimization algorithm. The literature is lacking in the application of the robust combinatorial optimization algorithm to R&D project portfolio selection based on the generalized n-fold compound option model of Cassimon et al. (2004). Every framework from calculation of the n-fold compound option to solving robust combinatorial algorithm is programmed in Matlab software, since it can be used as a business support tool.

Increasing heat transfer rate in spiral heat exchangers is possible by using conventional methods such as increasing number of fluid passes and counter flowing. In addition, newer ideas such as using pillows as baffles in the path of cold and hot fluids and using nanofluids can increase heat transfer rate. The purpose of this study is to simulate turbulent flow and heat transfer of two-phase water-silver nanofluid with 0-6 Vol.% nanoparticle concentration in a 180° path of spiral heat exchanger with elliptic pillows.

In this simulation, the finite volume method and two-phase mixture model are used. The walls are subjected to constant heat flux of q″ = 150,000 Wm⁻². The inlet fluid enters curves path of spiral heat exchanger with uniform temperature T_in = 300 K. After flowing past the pillows and traversing the curved route, the working fluid exchanges heat with hot walls and then exits from the section. In this study, the effect of radiation is disregarded because of low temperature range. Also, temperature jump and velocity slipping are disregarded. The effects of thermophoresis and turbulent diffusion on nanofluid heat transfer are disregarded. By using finite volume method and two-phase mixture model, simulations are performed.

The results show that the flow and heat transfer characteristics are dependent on the height of pillows, nanoparticle concentration and Reynolds number. Increasing Reynolds number, nanoparticle concentration and pillow height causes an increase in Nusselt number, pressure drop and pumping power.

Turbulent flow and heat transfer of two-phase water-silver nanofluid of 0-6 per cent volume fraction in a 180° path of spiral heat exchanger with elliptic pillows is simulated.

Although recent years have shown increasing popularity of e-commerce worldwide, there is still a lack of studies comprehensively exploring trust issue in e-commerce. Based on trust transfer theory and signaling theory, the purpose of this paper is to present an integrated research model to test the relationships between trust dimensions and e-loyalty, interactions among trust dimensions, as well as antecedents of different trust dimensions.

Data were collected through a web-based survey in Chinese markets and structural equation modeling with partial least squares was used to analyze the data.

The results identified that three trust dimensions all have significant impacts on e-loyalty, and relationships existed in different trust dimensions. Moreover, information quality and security protection are important factors determining institutional trust while store reputation is the most salient factor determining interpersonal trust.

This research contributes to the body of knowledge on trust by exploring the nature of trust with a multidimensional scale. Another theoretical contribution is the provision of a comprehensive understanding of the trust antecedents in e-commerce. Furthermore, this research benefits the companies doing e-businesses by allowing them to better understand how to improve consumers’ trust in the online environment and thus to retain and attract more loyal customers and succeed in online businesses.