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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.

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.

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.

The purpose of this paper is to demonstrate empirically that corruption causes significant and sizeable macroeconomic costs to countries in terms of economic activity and economic growth. The authors modeled corruption building on the endogenous growth literature and finally estimated the baseline (bribes paid to public officials) macroeconomic cost of corruption using Argentina 2004-2015 as a case study.

The authors laid the foundations of a new methodology to account corruption losses using data from the national accounts and judiciary investigations within the framework of the Organisation for Economic Cooperation and Development (OECD) non-observed economy (NOE) instead of subjective indicators as in the earlier literature. They also suggested a new method to compute public expenditures overruns, including but not limited to public works.

The authors found the costs stand at a minimum accumulated rate of 8 per cent of gross domestic product (GDP) or 0.8 per cent yearly. These findings provided a corruption cost floor and were consistent with earlier research on world corruption losses estimated at 5 per cent by the World Economic Forum and with the losses estimated at between a yearly rate of 1.3 and 4 per cent and 2 per cent of GDP by Brazil and Peru’s corruption, respectively.

The authors would need to extend the application of their new suggested methodology to further countries. They are working on this. They would need to develop the methodology in full to compute the public works overruns input to future econometric work.

In this paper, the authors make a threefold contribution to the literature on corruption and growth: first, they laid the foundations toward a new methodology to make an accounting of the corruption costs in terms of GDP consistent with the national accounts and executed budgets; on the one hand, and the OECD NOE framework, on the other. The authors named those corruption costs as percentage of GDP the “corruption wedge.” Second, they developed an example taking corruption events and a component of their total costs, namely, the bribes paid to public officials, taking Argentina 2004-2015 as a case study. Finally, they plugged the estimated wedge back into an endogenous growth model and calibrated the growth–corruption path simulating two economies where the total factor productivity was different, at different levels of the corruption wedge.

Money laundering is an activity where illegal proceeds are hidden. This often leads to a reduction in government revenue and loss of government control of public funds. This study aims to identify the important sources of growing demand for money laundering in developing countries. Further, it identifies the factors that reduce the impact of sources of demand for money laundering.

This study used the panel approach of feasible generalized least square to investigate the growing demand for money laundering in 62 developing countries and provides a moderation-based solution for managing the demand factors.

The empirical results of this study indicate that there are two sources that increase the demand for money laundering in developing countries. This includes a high tax rate on profit linked with private firms and businesses and diversion of public funds related to government officials and politicians. The results indicate that profit tax and diversion of funds increase the demand for money laundering. The profit tax-based money laundering can be moderated by the quality of the education system and the diversion of public funds and money laundering can be moderated using bureaucracy quality.

This is one of the first studies to empirically estimate the impact of two important sources (i.e. diversion of public funds by government officials and politicians and a high tax rate) that create demand for money laundering in developing countries. The findings help developing countries’ governments formulate policies and curb the growing demand for money laundering.

The purpose of this paper is to establish a three‐dimensional service house of quality (HOQ). The new service HOQ adds a dimension of quality economics to solve the problems of economic evaluation in the process of transferring customer requirements into service characteristics by traditional HOQ.

Based on the traditional two‐dimensional HOQ, this paper constructs a three‐dimension service HOQ by adding an economic dimension into the traditional structure, so that the transformation process from customer requirements into service characteristics can be evaluated with quality economic perspective. The key concern of this new model is to balance the quality improvement and economic gain of a service. The other improvement of this paper is that it uses structural equations to present the coefficient matrix in the new HOQ model to avoid human errors in the evaluation. A case study is used to verify the effectiveness of the new model.

Quality gains and costs should be considered in service design and quality improvement. The three‐dimensional service HOQ uses the dimension of quality economics to balance customer requirements and service characteristics, which is more effective than the traditional one.

The method exposed in the paper can be used by service companies for decision making in service design and quality improvement.

This paper establishes a new three‐dimensional HOQ, by which quality economics can be effectively analyzed in service design and quality improvement.