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How a micro-founded discipline such as economics could deal with the increasing global economic reality? This question has been asked frequently since the last economic crisis that appeared in 2008. In this challenging context, some commentators have turned their attention to a new area of knowledge coming from physics: econophysics which mainly focuses on a macro-analysis of economic systems. By showing that concepts used by econophysicists are consistent with an existing economic knowledge (developed by J.S. Mill), the purpose of this paper is to claim that an interdisciplinary perspective is possible between these two communities.

The authors propose a historical and conceptual analysis of the key concept of emergence to emphasize the potential bridge between econophysics and economics.

Six methodological arguments will be developed in order to show the existence of conceptual bridges as a necessary condition for the elaboration of a common language between economists and econophysics which would not be superfluous, in this challenging context, to clarify the growing complexity of economic phenomena.

Although the economics and econophysics study same the complex economic phenomena, very few collaborations exist between them. This paper paves a conceptual/methodological path for more collaboration between the two fields.

Bulk shipping mostly facilitates the smooth flow of raw materials around the globe. Regardless, forecasting a bulk shipbuilding orderbook is a seldom researched domain in the academic arena. This study aims to pioneer an econophysics approach coupled with an autoregressive data analysis technique for bulk shipbuilding order forecasting.

By offering an innovative forecasting method, this study provides a comprehensive but straightforward econophysics approach to forecast new shipbuilding order of bulk carrier. The model has been evaluated through autoregressive integrated moving average analysis, and the outcome indicates a relatively stable good fit.

The outcomes of the econophysics model indicate a relatively stable good fit. Although relevant maritime data and its quality need to be improved, the flexibility in refining the predictive variables ensure the robustness of this econophysics-based forecasting model.

By offering an innovative forecasting method, this study provides a comprehensive but straightforward econophysics approach to forecast new shipbuilding order of bulk carrier. The research result helps shipping investors make decision in a capital-intensive and uncertainty-prone environment.

Mobile phones are radically transforming micro-finance in Sub-Saharan Africa, and Kenya, in particular. The introduction of the micro-financial transaction mobile phone application, “MPesa,” created a means to facilitate micro-transactions without the need for an intermediary, such as a banking system. The purpose of this paper is to posit an econophysics model to predict the value of Mpesa for Kenyan and South African consumers. The econophysics framework posits several fitness matrices and a distance measure that can account for the concepts of mass, distance, momentum, velocity, action, and force. The authors begin with a table of the match between the physics concepts and the economic concepts followed by the vector model that utilizes these concepts for the MPesa application case. In this paper, the authors will argue that MPesa succeeded in Sub-Saharan African countries, such as Kenya, because the fit between what this group of customers needed and the solutions Safaricom’s MPesa offered was a better fit with a smaller distance to adoption than in the South African case.

The research develops an econophysics approach to the assessment of micro-finance development in Sub-Saharan countries.

The research shows clearly the reasons of the success of MPesa in Kenya in comparison of its relative failure in South Africa: the distance between customers’ expectations and the system supply.

The research is limited to two case studies and needs to be extended to other contexts, in order to demonstrate its robustness, especially with regard to the intangible dimension, e.g., the distance between a system potential and what it really offers.

The research shows the importance of system’s characteristics in its success.

The social implications are very high, especially in this case, where micro-finance is a high stake for developing societies.

This is one of the first works to develop an econophysics approach for the evaluation of the key characteristics of a system.

The term “agent-based modelling” (ABM) is a buzzword which is widely used in the scientific literature even though it refers to a variety of methodologies implemented in different disciplinary contexts. The numerous works dealing with ABM require a clarification to better understand the lines of thinking paved by this approach in economics. All modelling tasks are a means and a source of knowledge, and this epistemic function can vary depending on the methodology. this paper is to present four major ways (deductive, abductive, metaphorical and phenomenological) of implementing an agent-based framework to describe economic systems. ABM generates numerous debates in economics and opens the room for epistemological questions about the micro-foundations of macroeconomics; before dealing with this issue, the purpose of this paper is to identify the kind of ABM the author can find in economics.

The profusion of works dealing with ABM requires a clarification to understand better the lines of thinking paved by this approach in economics. This paper offers a conceptual classification outlining the major trends of ABM in economics.

There are four categories of ABM in economics.

This paper suggests a methodological categorization of ABM works in economics.

The purpose of this paper is to perform Shariah review of Brownian motion that is used for prediction of Islamic stock prices and their volatility.

It uses the Shariah compliant development model guidelines to review the Brownian motion and its applications.

The model of Brownian motion does not involve any variable that renders it non-Shariah compliant; neither all applications of Brownian motion are Shariah compliant. Because the model is based on stochastic properties that involve randomness, therefore the issue of gharar takes the utmost important to handle in the applications of the model. The results need to be analyzed strictly in accordance with the Shariah whether they create any element of gharar or uncertainty in case of expected price and volatility estimates.

The research suffers from the limitation that it analyses only one model of physics, i.e. Brownian motion model from Shariah perspective.

The research opens an area for Shariah analysis of results generated from the application of advanced models of physics on matters related to Islamic financial markets.

The originality of this study stems from the fact that to the best of the authors’ knowledge, it is the first study that extends Shariah guidelines into Financial physics for making the foundations of Islamic econophysics.

The purpose of this paper is to investigate the statistical correlation properties of the Shanghai Interbank Offered Rate (SHIBOR) interbank lending market.

The authors apply methods of correlation analysis, random matrix theory (RMT) and minimum spanning tree (MST) to investigate the correlation properties of Chinese interbank lending market and analyze how the SHIBOR panel banks behave in different market periods.

First, the largest eigenvalue λ ₁ is the index to describe the market mode of the whole market when all banks behavior collectively and λ ₁/N is a good estimator of the average correlation <C> of the correlation matrix. Second, notably, the authors find the “market mode” is weakened in two crises periods of 2008 stock market crash and 2009 Global Financial Crisis. This is significantly different from other market where the “market mode” is normally strengthened in crises periods. Third, the authors subtract the contribution of λ ₁, the second and third eigenvalue, λ ₂ and λ ₃, will fall outside of the predicted interval. And both λ ₂ and λ ₃ are getting times larger in the crises periods than in “Non-Crisis” period. Fourth, and in the MST analysis, the authors find again that the average distances of the MST are the times larger in crises periods than in “Non-Crisis” period and the second largest eigenvalue is a good estimator of the average distance of the MST.

According to the best knowledge, this paper is the first work on the study of the statistical properties of an interbank lending market using quotation level data of panel banks, which allows us to analyze the properties of the interest rate formation and how all panel banks behavior in different periods. This work is also the first study on the SHIBOR market using econophysics methods of correlation analysis, RMT and MST.

Technology‐based new ventures (TNVs) – which rely on entrepreneurial activities based on science and technology applications in newly created organizations to be successful – are important to current economic growth and innovation. Past research has looked at the importance of networks and social capital to TNV performance. Yet these studies rarely provide theoretical predictions of the attributes of network ties. This paper aims to bring TNV theory up to date with respect to twenty‐first century adaptation and complexity conditions.

The paper draws on new developments in complexity science (specifically scalability and scale‐free theories) and long‐standing first principles of efficacious adaptation to develop TNV‐relevant theory offering an alternative perspective on the impact of network ties on the performance of TNV.

It is argued that TNVs can achieve superior performance by developing and building moderate numbers of short‐term (and thereby weak) network ties. The theorizing calls for a new research agenda pertaining to TNVs, which are delineated. The paper also develops four propositions as part of setting forth an agenda for future research.

The paper updates the entrepreneurship and social network literatures by reshaping them with respect to the nonlinear order‐creation dynamics of complexity theory and scale‐free dynamics of econophysics. It focuses on the aspects of network theory that are especially likely to set in motion the complex adaptive systems dynamics essential to TNV performance. Therefore, the conceptual framework contributes to TNVs as a guide to achieving higher performance, effectiveness, and longevity in a rapidly changing world.

The purpose of this paper is to derive crucial insights from multi-scale analysis to detect equity return co-movements between Korean and emerging Asian markets.

Wavelet correlation, wavelet coherence and wavelet clustering measures are used to uncover Korean equity market interactions which are hard to see using any other modern econometric method and which would otherwise had remained hidden.

The authors observed that Korean equity market is strongly integrated with Asian equity markets at lower frequency scales and has a relatively weak correlation at higher frequencies. Further this correlation eventually grows strong in the interim of crises period at lower frequency scales. The authors, however, do not found any significant deviation in dendrograms generated in data clustering process from wavelet scale 2 to 6 which are associated with four and 64 weeks period, respectively. Overall the findings are relevant and have strong policy and practical implications.

The unique contribution of this paper is that it introduces wavelet clustering analysis to produce a nested hierarchy of similar markets at each frequency level for the first time in finance literature

This paper aims to present a framework enriching currency risk analyses based on information theory.

Information-theoretic measures of predictability (entropy rate) and co-dependence (mutual information) are used to enhance existing methods of analysing and measuring currency risk.

The currency exchange rates have varying degrees of predictability, which should be accounted for in currency risk analyses. In case of baskets of currencies, a network approach rooted in portfolio theory may be useful.

The currency exchange rate time series must be discretised for the information-theoretic analysis (although the results are robust). An agent-based simulation may be a necessary further study to show what the impact of accounting for predictability in managing currency risk is.

Practical analyses measuring currency risk should take predictability of currency rate changes into account wherever the currency exposure is actively managed.

The paper introduces predictability into measuring currency risk, which has previously been ignored, despite the nature of the risk being inherently tied to uncertainty of the currency rate changes. The paper also introduces a portfolio theory-based approach to quantifying currency risk, which accounts for non-linear co-dependence in the currency markets.

The purpose of this paper is to examine publication characteristics and dynamic evolution of the Industrial Management & Data Systems (IMDS) over the past 25 years from volume 94, issue 1, in 1994 through volume 118, issue 9, in 2018, using a bibliometric analysis, and identify the leading trends that have affected the journal during this time frame.

A bibliometric approach was used to provide a basic overview of the IMDS, including distribution of publication and citations, articles citing the IMDS, top-cited papers and publication patterns. Then, a complex network analysis was employed to present the most productive, influential and active authors, institutes and countries/regions. In addition, cluster analysis and alluvial diagram were used to analyze author keywords.

This study presents the basic bibliometric results for the IMDS and focuses on exploring its performance over the last 25 years. And it reveals the most productive, influential and active authors, institutes and countries/regions in IMDS. Moreover, this study detects the existence of at least five different keywords clusters and discovers how themes have evolved through the intricate citation relationships in IMDS.

The main contribution of this paper is the use of multiple analysis techniques from a complex network paradigm to emphasize the time evolving nature of the co-occurrence networks and to explore the variation of the collaboration networks in the IMDS. For the first time, the evolution of research themes is revealed with a purely data-driven approach.