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The study aims to construct an understanding of professional academic writing network structures to inform organisational strategic investment in academic staff development.

Longitudinal social network analysis is used to examine the personal-networks evident in the publication portfolios of a purposive sample of four international academics across each quartile of the SCOPUS defined area of General Nursing's top 100 authors.

Trends in the publication portfolios of elite academics across gender, sector and geographic location are presented. In the first years of successful writing for publication, authors collaborate within a single highly connected co-author network. This network will typically expand to include new co-authors, before additional separate co-author collaborations emerge (three- to four- years). Authors experience steady growth in co-author numbers four- to seven- years from first co-authored publication. After a period of rapid expansion, these collaborations coalesce into a smaller number of highly connected groups (eight- to ten- years). Most collaborations occur within the higher education sector and across multiple disciplines including medicine, social sciences and psychology. Male co-authors are disproportionately represented in what is a predominantly female profession.

The development of extended co-author networks, locally, internationally and across the higher education sector, enable authors to attain the marker of achievement required by universities and government funding bodies, namely sustained output of academic publications. Identified trends support the inclusion of investment in academic time and resources in higher education institutions strategic and operational plans to enable academic staff to develop interdisciplinary professional networks. In focussing this investment on gender equality, female academics will experience parity of opportunity in achieving their organisational and personal goals relating to professional academic writing. Medium-term investment may be required before the impact of that investment becomes apparent.

This is the first example of social network analysis used to determine characteristics of professional academic writing portfolios over time. Findings inform the type and range of investment required to facilitate academic staff writing activities, specifically those publishing in the area of General Nursing.

The Wikipedia (2008) entry for mathematical sociology cites four books with ‘mathematical sociology’ in the title: Coleman (1964), Fararo (1973), Leik and Meeker (1975) and Bonacich (2008). Fararo (1973, pp. 764–766) provides a guide to the literature in mathematical sociology covering journals, bibliographies, reviews and expository essays, readers, texts, original monographs and research papers. Many of the references are either broader than mathematical sociology, for example, concerning the behavioural sciences in general, or narrower, dealing with a particular topic within sociology, or concerning a related field such as social psychology. Three classical original monographs are identified: Dodd (1942), Zipf (1949) and Rashevsky (1951). Included in a second generation of monographs is Coleman's (1964) ‘An Introduction to Mathematical Sociology’. Could it be that this is the first use of the phrase ‘mathematical sociology’?

The main objective of this study is to explore the relationship between total quality management (TQM) practices and the business performance of Japanese‐owned manufacturers in the USA.

In this empirical study, 200 companies were chosen by random sampling from the universe group of 519 in August 2007. A total of 32 usable questionnaires were received, and the overall response rate was 16 percent.

The survey results show that TQM practices significantly influence the overall company performance of Japanese‐owned manufacturers in the USA. This implies that TQM is an effective method for improving business performance, regardless of where the company might be operating, as long as the TQM practices are appropriately implemented. In addition to the research data, findings from a field research also provide supplementary evidence to support this conclusion.

This study compares the findings from a recent survey conducted in the USA with the authors' previous study done in China. The survey uses the Malcolm Baldrige National Quality Award (MBNQA) criteria as a measuring scale, and the project adopts a pre‐tested questionnaire as a survey instrument, which has also been used in previous empirical studies.

The purpose of this paper is to find the determinants of participation and targeting efficiency of the following safety net programs in West Bengal: Mahatma Gandhi National Rural Employment Guarantee Act (MNREGA), self-targeted program; National Rural Livelihood Mission (NRLM), subsidy based livelihood program; Indira Awaas Yojona (IAY), targeted cash transfer program and Public Distribution System (PDS), targeted in kind transfer program.

The study is based on a household survey comprising 900 households across three Districts: Murshidabad, Nadia and Burdwan.

Benefits from MNREGA and PDS are not substantial, whereas financial benefits are substantial from NRLM and IAY. This paper shows that poor people have higher likelihood of participation in MNREGA and PDS. But, non poor get disproportionate benefits from IAY and NRLM both have been designed for the poor. Therefore, targeting cannot remove elite capture altogether. Socially down trodden section have higher participation in MNREGA and PDS, whereas people who are at upper tier of social hierarchy enjoy the benefits of IAY and NRLM. However, it cannot be said that these programs miss their target completely.

The study suffers from the usual limitations of sampling.

Programs targeted for the poor are being appropriated by the non poor. If there is better targeting money will be channelized to the desired beneficiaries and welfare will be enhanced.

The study has unearthed the underlying reasons behind why some safety net programs have better targeting and some safety net programs have poor targeting.

The purpose of this paper is to add to the debate concerning the merits of export promotion efforts by governments by investigating the effect of export promotion program (EPP) participation on the export performance of Dutch small and medium-sized enterprises (SMEs).

The authors confront participation data of an EPP targeting SMEs with rich firm-level data and use propensity score matching techniques combined with regression analysis.

The authors show that exports generated by participants do generally rise in the years after program entry, however, export growth does not outpace that of comparable, but unsupported firms. Nonetheless, there is some evidence suggesting that export shares in sales rise faster among program entrants, particularly in the first and second years after participation. Furthermore, the authors present evidence suggesting that the probability of becoming a permanent exporter is higher for participants relative to beginning exporters that did not receive support from the program.

The analysis contributes to the still relatively small literature dealing with the impact of government export promotion instruments on export performance using firm-level micro-data. The subject of analysis are Dutch small businesses. SMEs, particularly operating in advanced economies, are a group that is not frequently considered separately in this respect.

Examines the effects of decision unstructuralness (unstructuredness + noisiness) on decision‐support systems (DSS) adoption. Suggests that end‐users are sensitive to “unstructuralness” when they select a decision support approach. Problem structuring at the intelligence phase generates the first signal about DSS usefulness. If this signal is in favour of DSS, the manager either immediately adopts the DSS, or performs problem solving at the design phase. At this phase a new signal will be generated thus, confirming or denying DSS usefulness. This confirms that problem structuring prevails in making the DSS adoption decision. That is, in making the DSS adoption decision, priority is given to problem structuring in the intelligence phase.

Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.

There is a significant body of literature explaining how a free market for kidneys would eliminate both the economic and the medical shortage of kidneys and thus, in addition to supplying sufficient kidneys for those who become needy in the future, remove the entire backlog of 40,000+ patients waiting for a kidney transplant in the United States. This article is an attempt to fathom the financial and market processes that would evolve were a free market for kidneys to be permitted. Issues addressed include the types of institutions that would likely develop, how transactions would be facilitated, and what would happen to the price of kidneys both in the short and long term.

Records the research that investigates the differences in quality management between Shanghai and Norwegian manufacturing companies. The research is based on a survey supported by the Norwegian Association for Quality Management (NFK) and the Shanghai Association for Quality Control (SAQC). The research reveals major differences between the two parties. Compared with their Norwegian counterparts, Shanghai companies place greater emphasis on quality control and statistical methods while neglecting customer satisfaction and quality assurance. The final conclusion is that, although managers appreciate the importance of quality management, quality management in Shanghai is still focused on internal quality control, which is still far from Total Quality Management (TQM). Practical implications for future improvement in Shanghai companies and foreign joint ventures in Shanghai are discussed. Future research is also discussed.