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Penn World Tables (PWT) data on output measured at international prices are the data most frequently used in cross‐country growth regressions. These data are subject to revision, and the amendments can be substantial for a minority of countries, although negligible for most. The purpose of this paper is to investigate the effect of data revisions on research results using the data.

Using Hanushek and Kimko's analysis of the relationship between growth and schooling quality and Sala‐i‐Martin's tests of model selection, the authors investigate how much the results of cross‐country growth regressions vary if the most recent vintage (6.2) of PWT data is used, rather than the previous vintage (6.1).

The variation is substantial enough to imply significant differences in research results using different vintages of the PWT data.

The results reinforce the case for examining the sensitivity of growth regressions to outliers, which may be subject to subsequent data revision that might substantially affect the conclusions.

Previous research has identified significant revisions between successive vintages of PWT growth data, but has implied that this is not likely to affect the results of cross‐country growth regressions based on long‐run averages rather than on annual data. The findings suggest that this is not necessarily the case.

The present study aims to develop a risk-supported case-based reasoning (RS-CBR) approach for water-related projects by incorporating various uncertainties and risks in the revision step.

The cases were extracted by studying 68 water-related projects. This research employs earned value management (EVM) factors to consider time and cost features and economic, natural, technical, and project risks to account for uncertainties and supervised learning models to estimate cost overrun. Time-series algorithms were also used to predict construction cost indexes (CCI) and model improvements in future forecasts. Outliers were deleted by the pre-processing process. Next, datasets were split into testing and training sets, and algorithms were implemented. The accuracy of different models was measured with the mean absolute percentage error (MAPE) and the normalized root mean square error (NRSME) criteria.

The findings show an improvement in the accuracy of predictions using datasets that consider uncertainties, and ensemble algorithms such as Random Forest and AdaBoost had higher accuracy. Also, among the single algorithms, the support vector regressor (SVR) with the sigmoid kernel outperformed the others.

This research is the first attempt to develop a case-based reasoning model based on various risks and uncertainties. The developed model has provided an approving overlap with machine learning models to predict cost overruns. The model has been implemented in collected water-related projects and results have been reported.

This article describes an important project in the history of preservation of Egypt's culture heritage. Initiated by the Egyptian Ministry of Culture and executed by the Cabinet Information and Decision Support Center (IDSC), the project involves the Cairo Egyptian museum that contains the world largest collection of ancient Egyptian antiquities (160,000 objects). A major problem in the museum is the lack of a standardised approach for registration, resulting in a variety of unrelated registration schemes and the non‐existence of efficient tools for information dissemination. This project aims to resolve these problems. A team of Egyptologists, museum curators and system analysts, designers and developers defined the basis for work and specified project challenges which included the indexing of all museum objects ensuring cross‐referencing between already used registration schemes. The result has involved the use of multimedia computer technology to establish a complete database of museum objects (text, image and sound) and various cultural products, in addition to the establishment of required procedures and standards to organise the internal museum workflow and the provision of training programmes for staff. The outcome of the project is expected to be profound in enabling researchers and curators to have instant access to any object in the museum and providing the museum's visitors and public with a wealth of information about ancient Egypt.

The purpose of this study is to analyze the author’s experience related to several attempts of getting approved a paper of their authorship about gender and organizations by the lens of a researcher trying to meet his goal.

Throughout the endeavor, the author received substantial feedback and evaluations from editors and reviewers that allowed him to understand better the motivation of those that are dedicated to carry out such task; enhance his work whenever was possible; increase his resilience and self-motivation; and identify several inconsistencies of the peer-review process. Furthermore, that ample opinionated material allowed him to conduct the current autoethnographic study.

Accordingly, the author’s findings identified three aggregate dimensions, namely, demotivating assessments, mixed perceptions and motivating assessments. Moreover, the author did not identify any trace of developmental review (help), bill of rights or notion of being an “artist,” as some scholars suggest, from both the reviewers’ or editors’ part, but only from a specific journal’s editor and one of its reviewers. On the one hand, the majority of the reviewers/editors showed a harsh view about the author’s work or even a lack of interest to ponder his arguments and difficulties to carry out that study. Even though the author alluded to the limitations and unsurmountable hurdles that he faced along the way, they showed neither sympathy nor comprehension to his comments. On the other hand, it was not an easy task to the author to sift the hints provided by them.

Nonetheless, the author also recognizes his own limitations that eventually affected his analysis and point of views. It is also worth noting that this method relies on a unique source (the author).

The author believes that his ideas and opinions have some base and merit. Rather, his findings embrace profound implications for reviewers and editors, particularly in terms of how they perform their work.

To the best of the author’s knowledge, this is the first endeavor focusing on peer-review system related to organizational studies and grounded in an autoethnography approach. Therefore, their contribution is derived from a researcher that is familiar with the system and its flaws.

Social media platforms allow near‐unfettered creation and exchange of user generated content (UGC). Drawing from network science, the purpose of this paper is to examine whether high and low quality UGC differ in their connectivity structures in Wikipedia (which consists of interconnected user generated articles).

Using Featured Articles as a proxy for high quality, a network analysis was undertaken of the revision history of six different language Wikipedias, to offer a network‐centric explanation for the emergence of quality in UGC.

The network structure of interactions between articles and contributors plays an important role in the emergence of quality. Specifically the analysis reveals that high‐quality articles cluster in hubs that span structural holes.

The analysis does not capture the strength of interactions between articles and contributors. The implication of this limitation is that quality is viewed as a binary variable. Extensions to this research will relate strength of interactions to different levels of quality in UGC.

The findings help harness the “wisdom of the crowds” effectively. Organisations should nurture users and articles at the structural hubs from an early stage. This can be done through appropriate design of collaborative knowledge systems and development of organisational policies to empower hubs.

The network centric perspective on quality in UGC and the use of a dynamic modelling tool are novel. The paper is of value to researchers in the area of social computing and to practitioners implementing and maintaining such platforms in organisations.

Cyclical fluctuations in the level and rate of growth of economic activity have long been a feature of the British economy. The ability to forecast “turning points” (peaks and troughs) in business activity is of crucial importance for changes in companies' stockholding policy, hiring policy, capital budgeting, and many other aspects of corporate appraisal.

Britain is currently undergoing a severe economic recession which has increased the number of registered unemployed to over 3 million. Employment has fallen dramatically, with certain manufacturing industries recording employment declines of over 40 per cent since 1978. This article examines recent trends in retail employment and is based on a more detailed paper on retail employment and the recession presented to the Annual Conference of the Institute of British Geographers in January.

To examine whether both the value relevance of accounting information, and the quality of earnings affect financial analysts' revisions of forecast annual earnings per share soon after an earnings release.

For firms whose accounting earnings provide either a basis for firm valuation or new information, analysts are predicted to revise earnings forecasts in response to the magnitude of surprise in the earnings release. Using publicly available data, regression analysis explores the influence of earnings response coefficients (ERCs), unexpected earnings, and interactions between ERCs, the association between earnings and returns, and unexpected earnings on forecast revisions after earnings announcements.

Empirical tests demonstrate a positive relation between the percentage of analysts revising forecasts soon after interim earnings announcements and firm‐specific ERCs, the interaction between the magnitude of earnings surprises, ERCs, and earnings‐returns associations, and pre‐announcement dispersion in forecasts. The results suggest that usefulness of earnings releases is related to the magnitude of new information in the release, the persistence of earnings innovations, the firm‐specific mapping between earnings and returns, and prior uncertainty about earnings.

This paper examines forecast revisions only soon after earnings announcements. Future research should examine more general determinants of analysts' forecast revision activity.

This paper provides evidence about determinants of forecast revision frequency, a measure of how actively financial analysts provide information, an extension of prior research that focuses on analyst following as a measure of information environments.

World over, change of base year in the gross domestic product (GDP) is a standard practice of GDP estimation. However, unless a consistent series of GDP is released with respect to the new base for the earlier period, the existence of multiple growth rates creates problems for applied researchers, policymakers and the general public alike. Faced with such a menu of GDP series researchers often try to interpolate a consistent series of GDP. The main purpose of this paper is to analyses the nature of the data generating process of such multiple interpolated series of quarterly growth rates and tries to discern the consistency of such processes.

The present paper tries to look into the statistical implications and complications of such interpolated quarterly GDP/growth series in India in terms of three series of GDP, namely, with 1999–2000, 2004–2005 and 2011–2012 as its bases.

The analysis reveals that as a result of a change of base year, the nature of the data generating process of the old and new GDP series could undergo changes and experience different breakpoints. While all these conclusions seem to be valid for GDP growth at quarterly intervals, taking the data at annual frequency is less problematic.

The observation suggests that in most applied work, researchers may not have the luxury of only working with annual data and certain consistency checks will be necessary to check the veracity of the results based on quarterly data with those based on annual data. Second, moving forward it may be useful for the Authorities to make a transition to a chain-based linking method rather than fixed time-period-based bases as is currently done.

The analysis of Indian GDP in this paper is, perhaps, indicative of the fact that usage of quarterly GDP data is to be handled with caution and it is preferable that any serious empirical analysis uses annual GDP data whenever it is available/feasible. The comparison of GDP growth rates at different frequencies and examining the true nature of the process are quite unique in their contribution towards empirical macroeconomic research.

The forecast revision process is shaped by the environment in terms of the nature of the revision activity and in terms of its perceived effectiveness. A study on forecast revision focuses on the variables that describe the market situation for a product and so shape the context within which sales forecasting takes place, using a study of manufacturing companies operating in the UK health care industry. The three most important environmental factors that influence the revision process are the number of competitors in the market, the degree of market concentration and the intensity of non‐price competition.