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In this paper we give a synoptic view of the growth of the text processing technology of information extraction (IE) whose function is to extract information about a pre‐specified set of entities, relations or events from natural language texts and to record this information in structured representations called templates. Here we describe the nature of the IE task, review the history of the area from its origins in AI work in the 1960s and 70s till the present, discuss the techniques being used to carry out the task, describe application areas where IE systems are or are about to be at work, and conclude with a discussion of the challenges facing the area. What emerges is a picture of an exciting new text processing technology with a host of new applications, both on its own and in conjunction with other technologies, such as information retrieval, machine translation and data mining.

Despite the widespread study and application of public-private partnerships (PPPs) since the 1980s, the field lacks a universally accepted definition that captures the concept's complexity. This study aims to offer a definition and foster a more substantive and comprehensive discourse on PPPs to improve communication and understanding between academics and practitioners from diverse disciplines and legislative backgrounds.

Grounded in the family-resemblance concept proposed by German philosopher Ludwig Wittgenstein, this study conducts a comprehensive literature review to identify core and non-core elements frequently cited in PPP descriptions. The authors used these findings to develop the PPP sunflower model as a structured framework for defining PPPs.

The analysis elucidates six core elements consistently present in PPP descriptions: clarity of roles and responsibilities, appropriate risk allocation and sharing, injection of expertise and resources, cooperation and teamwork, a bundle of services, and long-term contracts. Coupled with identified non-core elements, these core components comprise the PPP sunflower model, a structured framework for defining PPPs that accommodates their multi-faceted nature.

The PPP sunflower model distinguishes itself as a unique contribution to the PPP literature. It offers a rigorous theoretical framework that can elucidate the complexity of PPPs for various stakeholders. The model serves as a practical tool for evaluating the authenticity and viability of PPP projects. The study's novelty lies in its adoption of the family-resemblance concept, thereby providing a comprehensive, multi-dimensional framework that enhances the understanding of PPPs across different disciplines and legislative contexts.

The purpose of this article was to evaluate the causal influence of Lean management practices on knowledge waste within the context of higher education institutions (HEIs). The peculiarities of knowledge impress upon organizations the need to think about reducing knowledge waste as a crucial practice. The Lean philosophy and practices therefore stand out as an appropriate management perspective, particularly given Lean's focus on waste elimination. However, little is known about the influence of Lean practices on reducing knowledge waste.

A quantitative research instrument was distributed to professors and technical and administrative staff across three types of HEI in the State of Rio Grande do Sul, Brazil. The validated and pretested survey was circulated to the target population via an online method to explore eight constructs and 38 items concerning Lean and knowledge and waste.

The results of the survey indicated that all hypotheses were supported. The sum total of 837 responses showed that the Lean relationships (internal organizational paths) were more obvious where leadership support proved to have a positive effect on continuous improvement, training, and customer involvement. Moreover, the significant and negative effects of the Lean practices studied on knowledge waste was also supported, including for example, the interaction between HEIs and its client base.

HEIs are knowledge generators. Therefore, the necessity of avoiding and reducing knowledge waste is even greater. This study also differentiates itself from the “traditional” knowledge loss studies by investigating knowledge while the employees are still part of an organization and not after they have left taking the knowledge away with them.

Accumulation of tolerances on components of sub‐assemblies has caused problems in automating assembly. Marposs has found a way round.

One of the noteworthy developments in the world economy is the cryptocurrency in general and the bitcoin in particular. Although several types of cryptocurrency are in operation in the current digital economy, the most prevalent is the bitcoin, which was launched formally in 2009 by an individual or group known under the pseudonym Satoshi Nakamoto. The value of bitcoin has increased to such an extend that it reached 19.7 billion US dollars by January 2, 2018 (Statista, 2018). As the bitcoin price touches a new high day by day, various terrorist organizations are using this cryptocurrency to anonymously finance their grotesque terrorist activities around the world by bypassing the surveillance mechanism of the banking system of the respective countries. Against this backdrop, this chapter aims to understand the mechanism of cryptocurrencies in general and the bitcoin in particular. Finally, it also endeavors to identify the trend of the bitcoin economy and its impact on nefarious activities in general and terrorism financing in particular. It has been revealed from the study that cryptocurrency economy has become so popular across the world that it has created an alternative virtual economy devoid of regulations from a specific country or a group of countries. By using vector error correction model (VECM), it had been observed that there exists a statistically significant long-run association between terrorist incidences and bitcoin transaction/circulation in the panel of 12 countries for 2010–2016. However, there is a huge concern over its way of operation and its unholy nexus with terrorism financing.

Job finding and separation are not well studied in economies with high labor informality. In this chapter, we contribute to filling the gap in the literature of labor turnover, proposing a methodology to estimate both indicators in an economy with high informality. To this end, we estimate indicators of job finding and separation rates for Peru's developing economy, in which labor informality stands at 70%. We find that, on average, these indicators in the formal sector are similar to those estimated in developed economies; however, in the informal sector, the calculated indicators are approximately two times higher than those of the formal sector. The two indicators show considerable heterogeneity in the informal sector according to several observable categories; in addition, the separation rate is countercyclical, and the finding rate is procyclical, this cyclicality being greater in the formal sector.

This study aims to examine the nonlinear threshold effect of shadow economy on sustainable development in Africa while providing additional evidence on how this nonlinear threshold effect play out in economies with high and low developed financial/credit markets.

This study uses 37 African economies between 2009 and 2017 in a dynamic GMM panel model that controls for country, year and technological effects to ensure consistency and reliability of results and findings.

The results reveal that there is an inverted nonlinear U-shape nexus between the size of shadow economy and sustainable development in both short run and long run in Africa and across economies with high and low developed credit/financial market. Also, the threshold points beyond which the size of shadow economies dampens sustainable development is lower for economies with high financial/credit market development and higher in the long run.

These results have policy implications and recommendations and suggest that shadow economies can be beneficial to sustainable development particularly when the size of shadow economies are restrained from increasing beyond certain thresholds/levels. Moreso, to restrict the adverse effect of shadow economies on sustainable development, policymakers can rely on developing their financial/credit markets to tame the destructive nature of shadow economies on sustainable development. These results are robust to technological, year/time and country effects.

To the best of the author’s knowledge, this study examines for the first in the context of Africa, the nonlinear effect of shadow economies on sustainable development under low and high developed financial markets.

This paper aims at assessing the impact of a number of behavioral interventions on the willingness of informal businesses, in the Egyptian informal sector, to join the formal sector.

This paper uses an experimental methodology to examine the impact of behavioral interventions on the formalization of the Egyptian informal sector. Specifically, it conducts a survey experiment on a total of 240 informal businesses, operating in the Egyptian informal sector. The primary data collected from the survey experiment is then analyzed using a binary logistic regression to assess the impact of the behavioral primes on the probability of joining the formal market.

The empirical findings of the survey experiment indicate that the biggest obstacle facing informal businesses is finding a formal source of finance that could help them in penetrating the market. Providing informal businesses with information on funding opportunities offered by the ministry of micro, small and medium enterprises (MSME) significantly increased the probability of joining the formal sector to benefit from this opportunity.

This paper is the first to apply behavioral primes, in the form of informational cues, to the Egyptian case of informal business owners. Previous research on the use of behavioral nudges and primes has focused mainly on the western economies.

Over one and half years have passed since the demonetization of Indian economy had occurred on November 8, 2016. The drastic step was initiated by the Prime Minister Narendra Modi with an intention to curb the “huge” circulation of illicit or “black” money of Indian economy by means of withdrawal of high value denominations of Rupees 500 and Rupees 1,000 from the supply of broad money (M3). This step helped to demonetize around 86 per cent value of total money supply leading to an unprecedented chaos in the economy and public life. The long delays in issuing fresh currency notes at the banks and ATMs further deteriorated the sudden economic crisis.

This research paper is aimed at exploring the proclaimed “efficacy” of demonetization policy as proposed by Reserve Bank of India by means of a mathematical approach and critically examines the effects of demonetization on the illicit money supply of Indian economy on the basis of macroeconomic theory.

From the mathematical model and related estimates, it may be easily deduced that the Indian policymakers deliberately hurled the masses in one of the gravest economic crises with a clear-cut intention of creating a political gimmick, when in reality, the proportion of illegitimate money supply was not even 1 per cent of total legitimate supply of money.

The analyses and findings related to this paper are based on mathematical modeling and logical interpretations. This paper is free of plagiarism as all the necessary sources and references are properly cited.

This paper aims to strive to model virtual trade resulting from time zone differences in an otherwise Heckscher–Ohlin set up which is absent in the literature. So, the paper adds some value to the existing literature on time zones (TZ) and trade.

A competitive general equilibrium model is developed first to capture the effect of TZ differences on virtual trade. Then the authors examine, in brief, if distance can be accommodated in such framework. Finally, the authors extend the model to incorporate informality.

It is seen that exploitation of time zone difference benefits skilled labor and hurts capital under reasonable assumption. In what follows, time zone difference exploiting sector expands, whereas the other sector contracts. Then, the model has been extended to examine how distance may also lead to similar outcomes. In addition, the model is further modified to explore the effect of virtual trade in an informality and associated extortion ridden economy. Interestingly, virtual trade turns out to be beneficial to unskilled workers as well, and leads to a fall in the number of extortionists, though informal production is augmented.

This model is a competitive model that may not clearly reflect the realistic world. However, interestingly this may form the basis of looking into some other appealing dimensions of the real world.

TZ and related communication-cost-driven trade arguments are relatively less explored theoretically. Therefore, the work adds some value to the theoretical understanding of outsourcing in service trade that uses day-night differences across the globe.