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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.

This study aims to analyze the complexities of the Brazilian soybean supply chain (SSC) and develop strategic interventions to improve the origin system’s performance.

This study used stakeholder interviews to identify the SSC bottlenecks and determine and assess drivers of competitiveness. A methodological framework based on the systems thinking approach for developing long-term structural changes was used. The problem was structured using behavior over time graph and causal loop modeling to propose three investment strategies to solve the logistics problem in SSC.

This study highlights the gaps in coordination between stakeholders and the public sector regarding the public policy for infrastructure investment. Three strategic interventions were developed to address the agro-industrial logistical problem, namely, investment in storage, multimodal transport systems and improvements in existing transport infrastructure. To overcome transport and storage logistics limitations, the authors suggest different forms of partnerships, including public-private partnerships.

This research is limited to evaluating an agricultural commodity (soybean) and does not include its by-products. The sample of stakeholders was limited and the boundary of analysis was Brazil. Nevertheless, the study showed how strategic interventions could be developed following a holistic analysis.

The proposed integrated approach illustrates the development of three strategic initiatives. It can be implemented by stakeholders, including the public sector, which is the basis for providing assertive long-term investments in Brazilian logistics.

The SSC analysis could promote the implementation of systemically determined interventions and strategies. It could significantly improve the performance of agricultural systems and help the formulation of public policies aimed at rural development.

The use of system dynamics to identify intervention points is an essential contribution to mitigating the SSC’s hindrances. Moreover, the combining methodologies resulted in comprehensive intervention strategies.

According to the “strategic focus and future orientation” principle of the integrated reporting (<IR>) framework, <IR> should provide information useful to support investors in assessing the future financial performance of organizations. This study aims to support the operationalization of this function by improving the forward-looking orientation of the integrated report.

Basing on the backward- and forward-looking disclosure in <IR> and the dynamic resource-based view (DRBV), this study develops an explorative case study building a quantitative simulation model based on an integrated report.

This study provides useful insights into how operationalizing the <IR> “future orientation” and obtaining more quantitative information on the organization’s capacity to create value in the future by applying DRBV and quantitative simulation modeling.

The article presents one case study to explore the method suggested to improve the <IR> forward-looking orientation. Additional case studies applying the same research design should be certainly useful to refine the method.

Supporting the <IR> forward-looking orientation, this study provides additional information for the decision-making process of investors, thus contributing to the efficient and productive allocation of capital.

Few studies have investigated forward-looking information in integrated reports, highlighting the existence of an “information gap” referred to such disclosure. Overcoming these previous results, the study provides useful insights on how to improve the <IR> forward-looking orientation.

Asset-intensive organizations rely heavily on physical assets that are often expensive, complex and have a significant impact on organizational performance. Past introductions of critical assets in various industries showed that despite many preparations in maintenance and operations, shortcomings were identified after deployment resulting in unreliable performance. The main purpose of this qualitative study is to explore the factors that determine how asset-intensive organizations can achieve reliable outcomes in critical asset introductions despite random failures as a result of increasing complexity and infant mortalities.

To gain a detailed understanding of the issues and challenges of critical asset introductions, a case study in railways (rolling stock introductions) was conducted and analyzed using qualitative analysis.

The case showed that organizational factors were perceived as decisive factors for a reliable performance of the introduction, while the main focus of the introduction was on the asset and its technical systems. This suggests that more consideration toward organizational factors is needed. Therefore, a critical asset introduction framework was proposed based on 15 identified factors.

Reliable performance is often associated with technical systems only. This empirical study emphasizes the need for a more holistic perspective and the inclusion of organizational factors when introducing critical assets seeking reliable performance. This study demonstrated the application of the affinity diagramming technique in collectively analyzing the data adopting a multidisciplinary orientation.

This paper aims to identify the interaction of different intervention strategies implemented in Malaysia towards flattening the curve of COVID-19 cases. Since the outbreak of COVID-19, many approaches were adopted and implemented by the Malaysian government. Some strategies gained quick wins but with negative unintended consequences after execution, whereas other strategies were slow to take effect. Learning from the previous strategies is pivotal to avoid repeating mistakes.

This paper presents the cause, effect of and connection among the implemented COVID-19 intervention strategies using systems thinking through the development of a causal loop diagram. It enables the visualisation of how each implemented strategy interacted with each other and collectively decreased or increased the spread of COVID-19.

The results of this study suggested that it is not only essential to control the spread of COVID-19, but also to prevent the transmission of the virus. The Malaysian experience has demonstrated that both control and preventive strategies need to be in a state of equilibrium. Focusing only on one spectrum will throw off the balance, leaving COVID-19 infection to escalate rapidly.

The developed feedback loops provided policy makers with the understanding of the merits, pitfalls and dynamics of prior implemented intervention strategies before devising other effective intervention strategies to defuse the spread of COVID-19 and prepare the nation for recovery.

This study conducts a comparative analysis of the impact of educational mismatch on Spanish wages. This paper aims to focus on the industrial, construction and service sectors at three levels of disaggregation: sector, occupation and gender.

The over-education, required education and under-education (ORU model), was applied to data from the 2018 Spanish Wages Structure Survey conducted by the Spanish National Statistics Institute.

The industrial sector is the one that best manages over-education by offering the highest returns to each year of over-education. It is also the sector that most values the education of women, particularly those in highly qualified positions.

This study compares the wage effects of educational mismatch in the service, industry and construction sectors. Previous literature has ignored the latter sectors in this field of study, but the results of the present study show that the industrial sectors significantly value and remunerates worker education. Therefore, it may be worthy to focus certain economic and social policies on this sector, to contribute to reducing gender wage gaps and gender employment discrimination in the economy.

In this article we aim to understand how the network formed by fitness tracking devices and associated apps as a subset of the broader health-related Internet of things is capable of spreading information.

The authors used a combination of a content analysis, network analysis, community detection and simulation. A sample of 922 health-related apps (including manufacturers' apps and developers) were collected through snowball sampling after an initial content analysis from a Google search for fitness tracking devices.

The network of fitness apps is disassortative with high-degree nodes connecting to low-degree nodes, follow a power-law degree distribution and present with low community structure. Information spreads faster through the network than an artificial small-world network and fastest when nodes with high degree centrality are the seeds.

This capability to spread information holds implications for both intended and unintended data sharing.

The analysis confirms and supports evidence of widespread mobility of data between fitness and health apps that were initially reported in earlier work and in addition provides evidence for the dynamic diffusion capability of the network based on its structure. The structure of the network enables the duality of the purpose of data sharing.

This paper aims to investigate seven prominent translations of the Qur'anic verb-noun collocations into English (Pickthall, 1930; AL-Hilali and Khan, 1977; Ali, 1934; Arberry, 1955; Shakir, 1999; Sarwar, 1981; Saheeh International, 1997) to unfold their renditions of the style and meaning of such Qur'anic verb-noun collocation into English.

The study follows a corpus-based research in a sense that the study is conducted on seven translations of the Noble Qur'an that have been taken form The Qur'anic Arabic Corpus, using linguistic and exegetical analyses. Based on Reiss’ model of text analysis (2000), the author analyses the intralinguistic and extralinguistic features of the Qur'anic verb-noun collocations.

Findings reveal that linguistic and exegetical analyses are perquisites for adequate rendition, which prevent deviation in meaning and translation loss. It is also found that Qur'anic collocations use unique literary techniques and devices, which hinder their natural and adequate renditions into English.

The novelty of this study lies in studying the architectural design of the Qur'anic verb-noun collocations in terms of the unique selection of words and style. Such unique architectural design of such collocations creates monumental hindrances in their rendition into other languages, which have not been given due attention in translation studies.

This corpus-based study provides a descriptive account of the distribution of the polysemous noun nafs in two Arabic varieties, Modern Standard Arabic (MSA) and Classical Arabic (CA). The research objective is to survey the use of nafs as a reflexive marker in local binding domains and as a self-intensifier in NP-adjoined positions.

The consulted corpora are Timespamped JSI Web corpus for MSA and Quran corpus for CA. While attending to corpora size differences, MSA and CA exhibit a pattern of difference and similarity in nafs diffusion.

In the modern variety, nafs is pervasively used as reflexive marker in canonical binding domains, along with a less frequent, yet notable, intensifier user, and these uses are partially and cautiously attributed to the specific genre in which they occur. In CA, nafs is mainly recurrent as a polysemous noun, along with extensive use as a reflexive marker in local binding settings. As an intensifier, nafs is totally non-existent in the CA corpus, in the same way as it is in absentia in VP-constituent extraction in MSA.

Examining whether nafs, as a reflexive marker, deviates from canonical binding in Arabic the way English reflexive pronouns do. Building a general account of this distribution is relevant in understanding the explicit (syntactic) and implicit (discourse-based) dimensions of reflexive marker and self-intensifier processing and interpretation in Arabic as a first and second language.

High levels of child obesity alongside rising stunting and the absence of a coherent food policy have deemed UK’s food system to be broken. The National Food Strategy (NFS) was debated intensely in media, with discussions on how and who should fix the food system.

Using a mixed methods approach, the authors conduct framing analysis on traditional media and sentiment analysis of twitter reactions to the NFS to identify frames used to shape food system policy interventions.

The study finds evidence that the media coverage of the NFS often utilised the tropes of “culture wars” shaping the debate of who is responsible to fix the food system – the government, the public or the industry. NFS recommendations were portrayed as issues of free choice to shift the debate away from government action correcting for market failure. In contrast, the industry was showcased as equipped to intervene on its own accord. Dietary recommendations made by the NFS were depicted as hurting the poor, painting a picture of helplessness and loss of control, while their voices were omitted and not represented in traditional media.

British media’s alignment with free market economic thinking has implications for food systems reform, as it deters the government from acting and relies on the invisible hand of the market to fix the system. Media firms should move beyond tropes of culture wars to discuss interventions that reform the structural causes of the UK’s broken food systems.

As traditional media coverage struggles to capture the diversity of public perception; the authors supplement framing analysis with sentiment analysis of Twitter data. To the best of our knowledge, no such media (and social media) analysis of the NFS has been conducted. The paper is also original as it extends our understanding of how media alignment with free market economic thinking has implications for food systems reform, as it deters the government from acting and relies on the invisible hand of the market to fix the system.