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Crowdfunding (CF) is a digital-financial innovation that, bypassing credit crisis, bank system rigidities and constraints of the capital market, is allowing new ventures and established companies to get the needed funds to support innovations. After one decade of research, mainly focused on relations between variables and outcomes of the CF campaign, the literature shows methodological lacks about the study of its overall behavior. These reflect into a weak theoretical understanding and inconsistent managerial guidance, leading to a 27% success ratio of campaigns. To bridge this gap, this paper embraces a “complex system” perspective of the CF campaign, able to explore the system's behavior of a campaign over time, in light of its causal loop structure.

By adopting and following the document model building (DMB) methodology, a set of 26 variables and mutual causal relations modeled the system “Crowdfunding campaign” and a data set based on them and crafted to model the “Crowdfunding campaign” with a causal loop diagram. Finally, system archetypes have been used to link the causal loop structure with qualitative trends of CF's behavior (i.e. the raised capital over time).

The research brought to 26 variables making the system a “Crowdfunding campaign.” The variables influence each other, thus showing a set of feedback loops, whose structure determines the behavior of the CF campaign. The causal loop structure is traced back to three system archetypes, presiding the behavior in three stages of the campaign.

The value of this paper is both methodological and theoretical. First, the DMB methodology has been expanded and reinforced concerning previous applications; second, we carried out a causation analysis, unlike the common correlation analysis; further, we created a theoretical model of a “Crowdfunding Campaign” unlike the common empirical models built on CF platform's data.

In this study the authors aim to outline new ways of information extraction for automated valuation models, which in turn would help to increase transparency in valuation procedures and thus contribute to more reliable statements about the value of real estate.

The authors hypothesize that empirical error in the interpretation and qualitative assessment of visual content can be minimized by collating the assessments of multiple individuals and through use of repeated trials. Motivated by this problem, the authors developed an experimental approach for semi-automatic extraction of qualitative real estate metadata based on Comparative Judgments and Deep Learning. The authors evaluate the feasibility of our approach with the help of Hedonic Models.

The results show that the collated assessments of qualitative features of interior images show a notable effect on the price models and thus over potential for further research within this paradigm.

To the best of the authors’ knowledge, this is the first approach that combines and collates the subjective ratings of visual features and deep learning for real estate use cases.

This paper aims to develop a performance measure for Islamic banks (IBs) by harmonizing related studies. Furthermore, this work uses the developed yardstick to analyze the performance of a sample of 11 IBs from across different countries.

This paper uses the mix-mode method. The qualitative approach is engaged first to construct the IBs performance yardstick. Following this, the quantitative approach is applied through the use of the performance yardstick to measure the sample’s performance.

This study develops a maqāṣid-based performance yardstick adapted from previous works. The developed model in this study is called an integrated maqāṣid al-Sharīʿah--based performance measure (IMSPM). By using this performance measure, the present paper finds that the sample performed highest on the objective of nafs (self) over the three-year period. In addition, this study identifies the information which best indicates the sample’s performance during the analysis.

This paper uses the sample’s annual reports. The analysis is thus limited to informational disclosure.

Islamic banking and financial institutions may use the IMSPM to communicate a measurable report on their promotion of the maqāṣid al-Sharīʿah (objectives of Islamic law).

The evidence from 11 IBs is indicative of their efforts to realize maqāṣid al-Sharīʿah in the banking industry. This point may best challenge the practice of stigmatizing IBs for not being in line with the Sharīʿah (Islamic law) or of imitating conventional banks.

The novelty of this study lies in two points. First, this study harmonizes previous works to integrate financial and religious measures in a single yardstick. Second, by using the developed standard, this study offers a fresh insight into the global IBs’ performance, represented by 11 IBs worldwide.