Artificial intelligence (AI) is a powerful technology that can be utilized throughout a construction project lifecycle. Transition to incorporate AI technologies in the construction industry has been delayed due to the lack of know-how and research. There is also a knowledge gap regarding how...

Food Logistics 4.0 is a term derived from Industry 4.0 focusing on all the aspects of food logistics management based on cyber-physical systems. It states that real-time information and the interconnectivity of things, supplemented with novel technologies will revolutionise and improve the way...

Drawing upon more than 12 million observations over the period from 1996 to 2020, we find that allowing for nonlinearities significantly increases the out-of-sample performance of option and stock characteristics in predicting future option returns. Besides statistical significance, the...

Purpose - Big data analytics (BDA) capabilities can affect supply chain performance in several ways. The main purpose of this study was to understand how BDA capabilities could affect supply chain performance through supply chain resilience and supply chain innovation....

Financial innovation in the form of new delivery channels, products, and providers has helped push out the frontier of access to finance and thus increase the bankable and banked population. Mobile money and crowdfunding platforms are prime examples for this. The same financial innovation has...

Poverty statistics are conventionally compiled using data from household income and expenditure survey or living standards survey. This study examines an alternative approach in estimating poverty by investigating whether readily available geospatial data can accurately predict the spatial...

Due to SARS-CoV-2 pandemic, higher education institutions are challenged to continue providing quality teaching, consulting, and research production through virtual education environments. In this context, a large volume of data is being generated, and technologies such as big data analytics are...

The increased access and availability of information technology solutions have brought structural shifts in traditional business models, processes, and activities worldwide. As a result, the innovative ways of doing business and practices have disrupted the traditional businesses and...

We compare sparse and dense representations of predictive models in macroeconomics, microeconomics and ftnance. To deal with a large number of possible predictors, we specify a prior that allows for both variable selection and shrinkage. The posterior distribution does not typically concentrate...

Modern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics...

Not long before the coronavirus outbreak, fears about artificial intelligence (AI) algorithms and machines resulting in a jobless society were widespread. Concerns have resurfaced in light of the COVID-19 crisis potentially accentuating automation. This study utilises a novel big data set based...

Implementing the principles of green marketing started since the 70’s, once the social and societal marketing concepts were defined. The challenges brought around by globalization and the excessive pollution of the environment, that contemporary companies had to face, requested the...

With the rise of digital markets, the conventional wisdom was that big data was a new economic phenomenon that would allow incumbent firms with market power to entrench their market positions, foreclose competitors, and serve as a virtually insurmountable barrier to entry. This led to calls for...

Retail investors, on average, are known to be less informed. The democratized access to big financial data enabled by recent technological advances has the potential to make them better informed. At the same time, behavioral finance and economic theories postulate that such unprecedented access...

We study a model where firms accumulate data as a valuable intangible asset. Data accumulation affects firms' dynamics. It increases the skewness of the firm size distribution as large firms generate more data and invest more in active experimentation. On the other hand, small data-savvy firms...

Big data (BD) analytics is considered one of the most important general-purpose technologies of our era. Given the pervasiveness of BD across industries, both policy-makers and scholars have become particularly interested in assessing the effects of BD on firm performance. However, previous...

In this paper, a large amount of different financial and macroeconomic variables are used to predict the U.S. recession periods. We propose a new cost-sensitive extension to the gradient boosting model which can take into account the class imbalance problem of the binary response variable. The...