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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 paper brings together the literature on theories of complexity adaptive systems (CAS), develops an analytical framework, applies this framework to the development of tourism destinations and critically reflects on the use of this perspective.

This paper elaborates on a CAS perspective on destination development, to further develop complexity thinking in tourism studies. This approach enables to identify policy avenues geared towards improving destination governance and contributing to sustainable tourism development.

Theories of CAS offer an analytical lens to better understand destination development, drawing explicit attention to (1) the levels of the individual, (emergent) structures, the structure-agency interface and the system level, (2) the steps related to the process of adaptation that is critical for systems to survive and thrive in times of change and (3) the undervalued importance of considering the factor of time.

Applying CAS theories help to address a range of (policy) avenues to improve destination governance, contributing to a shift in focus from reactively fixing problems to proactively addressing the structural issue of adaptive capacity building. It shows that managing tourism destination as complex systems involves a set of conditions that are critical as well as difficult to meet in tourism practice.

Smallholder value chains are dynamic, changing over time in sudden, unpredictable ways as they adapt to shocks. Understanding these dynamics and adaptation is essential for these chains to remain competitive in turbulent markets. Many guides to value chain development, though they focus welcome attention on snapshots of current structure and performance, pay limited attention to the dynamic forces affecting these chains or to adaptation. The paper aims to discuss these issues.

This paper develops an expanded conceptual framework to understand value chain performance based on the theory of complex adaptive systems. The framework combines seven common properties of complex systems: time, uncertainty, sensitivity to initial conditions, endogenous shocks, sudden change, interacting agents and adaptation.

The authors outline how the framework can be used to ask new research questions and analyze case studies in order to improve our understanding of the development of smallholder value chains and their capacity for adaptation.

The framework highlights the need for greater attention to value chain dynamics.

The framework offers a new perspective on the dynamics of smallholder value chains.

This study aims to investigate how dynamic tensions between performance measurement system (PMS) uses enable organizations to achieve both exploitation and exploration and enhance firm performance.

The authors collected survey data on 153 Italian companies. Scales for each construct were validated through an exploratory factor analysis. Data on firm performance were cross-validated by using lagged accounting data. The authors tested our hypotheses using hierarchical ordinary least squares regressions, together with bootstrapping procedures for the test on mediation.

A diagnostic use of PMS has a positive association with both exploitation – e.g. reductions in total costs and lead times – and exploration, e.g. introduction of new products and extension of product ranges. The dynamic tension created by a joint diagnostic and interactive use has the strongest association with organizational ambidexterity, measured as the multiplicative interaction between exploration and exploitation.

If an organization or business unit is mainly pursuing exploitative goals, a mainly diagnostic use of PMS would be most suitable. If goals are both exploitative and explorative, a mix of diagnostic and interactive uses would be most effective.

This research helps reconcile conflicting views in the literature. The diagnostic use of PMS, far from acting as a “negative force,” appears to be necessary to guide opportunity search and to establish an appropriate scope for exploration-related activities. The authors’ focus on the uses of PMSs shows that ambidexterity is achieved through managerial capability, rather than just through the introduction of systems and structures.

This study advocates the importance of taking an evolutionary perspective in the strategic configuration of closed-loop supply chains (CLSC) in the transition to a circular economy. Building on the supply chain management and industrial dynamics research domains, an evolutionary analytical framework was developed and applied in the empirical context of the ongoing industrial transition to e-mobility.

This study is designed as an in-depth exploratory case study to capture the multi-layer dynamic complexities and their interplay in CSLC development. The empirical investigation was based on two-year interactions between the authors and various departments in a leading European heavy vehicle manufacturer. The proposed evolutionary analytical framework was used for investigating the dynamics of four CLSC configurations through ten possible trajectories.

The findings demonstrate that the evolution of each CLSC configuration comes with multiple challenges and requirements and point out the necessity for the co-development of technologies, product design and production, and infrastructure through long-term relationships among key supply chain actors. However, this evolutionary journey is associated with multiple dilemmas caused by uncertainties in the market and technology developments. All these factors were properly captured and critically analyzed, along with their interactions, thanks to the constructs included in the proposed evolutionary analytical framework.

The proposed evolutionary framework is applicable for examination of SC transformation in the context of market and technology development, and is particularly relevant for transitioning from linear SC to CLSC. The framework offers a single actor perspective, as it does not directly tackle dynamics and effects of actions taken by SC actors.

The developed framework can support SC managers in identifying, framing, and comparing alternative strategies for CLSC configuration in the transition process.

This study proposes the framework for understanding and guiding the evolutionary process of CLSC development. Its uniqueness lies in the integration of concepts from innovation and evolutionary theories coming from industrial dynamics and SCM literature streams.

In response, the purpose of this paper is to provide theoretical frameworks about the organizational uncertainty behind what and when to adopt blockchain technology and their implications on transaction costs. The immature nature and the absence of standards in blockchain technology lead to uncertainty in government organizations concerning the adoption (“what to adopt”) and the identification of the right time (“when to start”).

Using transaction cost theory and path dependency theory, this paper proposes two frameworks: to assess transaction cost risks and opportunities costs; and to depict four different types of transaction costs outcomes regarding blockchain adoption.

This paper identifies various theoretical concepts that influence blockchain adoption and combine the two critical constructs of “bounded rationality” and the “lock-in effect” to categorize the multiple transaction costs outcomes for blockchain adoption.

Although existing research in blockchain highlights mainly the potential benefits of blockchain applications, only a little attention has been given to frameworks that categorize potential transaction costs outcomes under uncertainty, in particular from organizational theorists.

Both frameworks advance the understanding of the decision-making behind blockchain adoption and synthesize the current literature to offer conceptual clarity regarding the varied implications and outcomes linked to the uncertainty regarding transactions costs stemming from blockchain technology.

The authors’ goal is to provide an overview and historical context for the various alternatives to the efficient market hypothesis (EMH) that have emerged over time. The authors found eight current alternatives that have emerged to address the EMH's flaws. Each of the proposed alternatives improves some of the assumptions made by the EMH, such as investor homogeneity, the immediate incorporation of information into asset values and the inadequacy of rationality to explain asset prices.

To come up with the list of studies relevant to this review article, the authors used three databases, namely Scopus, Web of Science and Google Scholar. The first two were mostly used to get peer-reviewed articles while Google Scholar was used to extract articles that are still work in progress. The following words were used as the search queries; “efficient market hypothesis” and “alternatives to the efficient market hypothesis”.

The alternatives to the EMH presented in this article demonstrate that market efficiency is a dynamic concept that can be best understood with a multidisciplinary approach. To better comprehend how financial markets work, it is crucial to draw on concepts, theories and ideas from a variety of disciplines, including physics, economics, anthropology, sociology and others.

The authors comprehensively summarise the current state of the behavioural finance literature on alternatives to the EMH.

This paper aims to inform the promotion of sustainable modes of transport. For this purpose, it deploys a means-ends framework as a type of second-order cybernetics and uses it to explore cognitive transport mode choice structures.

The empirical study relies on a purposive sample and a qualitative research methodology known as laddering. It is aimed at the identification and comparative analysis of the cognitive means-ends structures of transport users.

The results reveal more positive and complex associations for the car than for public transport. Two main positive means-ends structures are identified for public transport, one related with the relaxation and the other with doing useful things while travelling. Dominant positive structures for the car are related with self-confidence, satisfaction and personal freedom. Negative means-ends structures in addition reveal important justifications and rationalizations for car use.

Based on the identified distinct means-ends elements and structures, this study holds important implications for developing a communications strategy and policy interventions seeking to promote public transport.

Means-ends theory is proposed as an integrative cybernetic framework for the study of stakeholders’ (customers’) mental models. The empirical study is the first to concurrently and comparatively examine positive and negative means-ends chains for the car and for the public transport modes.

The purpose of this study is to analyze how sentiment affects economic activity in Brazil.

Based on a nonlinear autoregressive distributed lag (NARDL) model, this study examines in detail the short-term and long-term asymmetric impacts between the variables during the period from January 2007 to December 2020.

There are three main results of this study. First, sentiment is an important factor for economic activity in Brazil, and its effect possibly occurs through the channels of consumption and investment, which are the two main components of economic growth. Second, sentiment affects economic activity in different ways in the short and the long term: in Brazil, although in the short-term, immediate shocks of sentiment may be confusing, the negative shocks from previous periods have a negative impact on economic activity. Third, the effect of shocks of optimism and pessimism on economic activity is asymmetric, and in the long run, only shocks of optimism have a significant and positive impact.

The relationship between sentiment and economic activity is still a controversial issue in the literature and this study seeks to advance its understanding in Brazil.

The emergence of networks within education has been driven by a number of factors, including: the complex nature of the issues facing education, which are typically too great for single schools to tackle by themselves; changes to educational governance structures, which involve the hollowing out of the middle tier and the introduction of new approaches with an individualized focus; in addition is the increased emphasis on education systems that are “self-improving and school-led”. Within this context, the realization of teacher and school improvement actively emerges from establishing cultures of enquiry and learning, both within and across schools. Since not every teacher in a school can collaboratively learn with every other teacher in a network, the most efficient formation of networks will comprise small numbers of teachers learning on behalf of others.

Within this context, Professional Learning Networks (PLNs) are defined as any group who engage in collaborative learning with others outside of their everyday community of practice; with the ultimate aim of PLN activity being to improve outcomes for children. Research suggests that the use of PLNs can be effective in supporting school improvement. In addition, PLNs are an effective way to enable schools to collaborate to improve educational provision in disadvantaged areas. Nonetheless harnessing the benefits of PLNs is not without challenge. In response, this paper explores the notion of PLNs in detail; it also sheds light on the key factors and conditions that need to be present if PLNs are to lead to sustained improvements in teaching and learning. In particular, the paper explores the role of school leaders in creating meaningful two-way links between PLNs and their schools, in order to ensure that both teachers and students benefit from the collaborative learning activity that PLNs foster. The paper concludes by suggesting possible future research in this area.