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Manufacturing is undergoing major transformation due to the unforeseen challenges arising from the current trend of miniaturization, the emergence of new materials and the growing interaction between biologists and engineers to learn more from nature and living objects.Traditionally, a "top-down" approach has been used in manufacturing. Recently, engineers and scientists have begun exploring "bottom-up" approaches for manufacturing today's highly complex products. Further, these emerging processes are aimed to improve process efficiency and product quality.The aim of the Journal of Manufacturing Processes (JMP) is to exchange current and future directions of manufacturing processes research, development and implementation, and to publish archival scholarly literature with a view to advancing state-of-the-art manufacturing processes and encouraging innovation for developing new and efficient processes. The journal will also publish from other research communities for rapid communication of innovative new concepts. Special-topic issues on emerging technologies and invited papers will also be published.Papers relevant to the scope of JMP include, but are not limited to, the following areas:• Meso/micro/nano fabrication, including imprint lithography.• Advanced manufacturing processes, including mechanical, chemical and thermal processes.• Welding, joining and assembly at micro and macro scales.• Rapid prototyping, rapid manufacturing and repair, stereolithography and other 3-D fabrication techniques that can use optical projection.• Advanced embossing, casting, forming and molding processes at all scales.• Mono/multilayer functional coating processes.• Continuum and subcontinuum process modeling and simulation.• Manufacturing process monitoring, control and automation.• Tribology and wear issues relevant to manufacturing processes.Benefits to authorsWe also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our support pages: http://support.elsevier.com

The Journal of Mixed Methods Research (MMR) is an innovative, quarterly, interdisciplinary, international publication that focuses on empirical, methodological, and theoretical articles about mixed methods research across the social, behavioral, health, and human sciences. The journal's scope includes delineating where mixed methods research may be used most effectively, illuminating design and procedure issues, and determining the logistics of conducting mixed methods research.

JM2 provides a forum those in business and management modelling. It analyses the conceptual antecedents and theoretical underpinnings leading to research modelling processes which inform research and practice.

A central medium for the publication of important research in the general area of multivariate analysis, the Journal of Multivariate Analysis presents articles on fundamental theoretical aspects of the field as well as on other aspects concerned with significant applications of new theoretical methods. Although articles addressing univariate analysis are considered for publication, particular attention is given to papers that discuss problems concerned with more than one variable.In addition to helping to stimulate research in multivariate analysis, the journal aims to bring about interactions among mathematical statisticians, probabilists, and scientists in other disciplines broadly interested in the area.Research Areas Include:• Asymptotic theory• Bayes models• Cluster analysis• Decision theory• Discriminant analysis• Distributions and tests• Estimation• Factor analysis• Limit laws• Measures of association• Multidimensional scaling and general multivariate methods• Multivariate ANOVA• Sequential analysis• Stochastic analysis and inference• Testing of hypothesis• Time series

Journal of Nonparametric Statistics provides a medium for the publication of research and survey work in nonparametric statistics and related areas. The scope includes, but is not limited to the following topics: Nonparametric modelingNonparametric function estimationRank and other robust and distribution-free proceduresResampling methodsLack-of-fit testingMultivariate analysisInference with high-dimensional dataDimension reduction and variable selectionMethods for errors in variables, missing, censored, and other incomplete data structuresInference of stochastic processesSample surveysTime series analysisLongitudinal and functional data analysisNonparametric Bayes methods and decision proceduresSemiparametric models and proceduresStatistical methods for imaging and tomographyStatistical inverse problemsFinancial statistics and econometricsBioinformatics and comparative genomicsStatistical algorithms and machine learning.Both the theory and applications of nonparametric statistics are covered in the journal. Research applying nonparametric methods to medicine, engineering, technology, science and humanities is welcomed, provided the novelty and quality level are of the highest order. Authors are encouraged to submit supplementary technical arguments, computer code, data analysed in the paper or any additional information for online publication along with the published paper. 2009 5-year Impact Factor: 0.594169; 2010 Thomson Reuters, 2009 Journal Citation Reports174;All published research articles in this journal have undergone rigorous peer review, based on initial editor screening and anonymous refereeing by independent expert referees.DisclaimerTaylor & Francis makes every effort to ensure the accuracy of all the information (the 8220;Content8221;) contained in its publications. However, Taylor & Francis and its agents and licensors make no representations or warranties whatsoever as to the accuracy, completeness or suitability for any purpose of the Content and disclaim all such representations and warranties whether express or implied to the maximum extent permitted by law. Any views expressed in this publication are the views of the authors and are not the views of Taylor & Francis.

The mission of Journal of Operations Management is to publish original, high quality, operations management empirical research that will have a significant impact on OM theory and practice. Regular articles accepted for publication in JOM must have clear implications for operations managers based on one or more of a variety of rigorous research methodologies. JOM also publishes insightful meta-analyses of the OM literature, conceptual/theoretical studies with clear implications for practice, comments on past articles, studies concerning the OM field itself, and other such matters relevant to OM.Manuscripts accepted for publication meet one or more of the following characteristics:1. Rigorous studies that use various forms of empirical methodologies: case studies, sample surveys, laboratory experiments, econometric analysis, and ethnographic studies 2. Papers that use multiple methods for triangulation purposes3. Papers with relevant and refreshing results and perspectives4. Empirically-grounded analytical modeling studies5. Conceptual/theoretical papers that provide a reality check for how practice has evolved or how it might evolveAudienceThe primary audience includes researchers who are interested in advancing the OM/SCM field and practitioners who have a concern for keeping abreast of the state of the art in operations management. The journal presents to this audience the concepts, theories, and managerial perspectives that address currently cutting-edge issues in operations management and supply chain management.Policies, Aims and ScopeJOM's distinctive emphasis is on the management of operations and supply chains. Accordingly, the aim of JOM is to enhance the field of OM/SCM and develop generalizable theory, typically through the identification, analysis, and theorization of real OM/SCM problems.JOM seeks research that can help the audience develop a better conceptual base for understanding OM/SCM. The focus of articles for JOM should be on the managerial situation or the theory being studied rather than the solution techniques being developed or used. Highest priority is thus given to studies that are anchored in the real world and build, extend or test generalizable theories or frameworks of managerial significance. Most often such studies result from identifying an actual, new managerial situation for which existing theory is inadequate, thereby resulting in an addition to theory or testing multiple theories against actual managerial situations to determine their relevance.General topics covered by the journal, while not exclusive, include the following:• Operations processes in manufacturing and service organizations; • Upstream supply management;• Downstream demand management;• Operations strategy and policy;• Product and service design and development; • Manufacturing and service systems design; • Technology management for operations; • Multi-site operations management; • Capacity planning and analysis; • Operations planning, scheduling and control; • Project management; • Human resource management for operations; • Work design, measurement and improvement; • Performance measurement and productivity; • Quality management; • Purchasing/sourcing management; • Materials and inventory management; • Logistics, transportation, distribution, and materials handling; • International and comparative operations; • Operations and information management; • Sustainable supply chain operations;• Humanitarian/disaster relief operations;• Regulatory and environmental issues in operations.Published by Elsevier in collaboration with APICS, Educational & Research Foundation

The Journal of Optimization Theory and Applications publishes carefully selected papers covering mathematical optimization techniques and their applications to science and engineering. Typical theoretical areas covered in the journal include linear, nonlinear, mathematical, and dynamic programming. Among the areas of application covered are mathematical economics, mathematical physics and biology, and aerospace, chemical, civil, electrical, and mechanical engineering. The Journal of Optimization Theory and Applications journal publishes five types of contributions: survey papers, contributed papers, technical notes, technical comments, and book notices.

Successful organizations respond intelligently to factors which precipitate change. Economic climates, political trends, changes in consumer demands, management policy or structure, employment levels and financial resources - all these elements are constantly at play to ensure that organizations clinging on to static structures will ultimately lose out. But change is a dynamic and alarming thing - this journal addresses how to manage it positively, so that employees give their support and the positive goals set are worked towards with enthusiasm.

Aims and Scope

The Journal of Responsible Innovation ( JRI) provides a forum for discussions of the normative assessment and governance of knowledge-based innovation. JRI offers humanists, social scientists, policy analysts and legal scholars, and natural scientists and engineers an opportunity to articulate, strengthen, and critique the relations among approaches to responsible innovation, thus giving further shape to a newly emerging community of research and practice.  These approaches include ethics, technology assessment, governance, sustainability, socio-technical integration, and others. JRI intends responsible innovation to be inclusive of such terms as responsible development and sustainable development, and the journal invites comparisons and contrasts among such concepts. While issues of risk and environmental health and safety are relevant, JRI especially encourages attention to the assessment of the broader and more subtle human and social dimensions of innovation—including moral, cultural, political, and religious dimensions, social risk, and sustainability addressed in a systemic fashion.

JRI invites three kinds of written contributions: research articles of 6,000 to 10,000 words in length, inclusive of notes and references, that communicate original theoretical or empirical investigations; perspectives of approximately 2,000 words in length that communicate opinions, summaries, or reviews of timely issues, publications, cultural or social events, or other activities; and pedagogy, communicating in appropriate length experience in or studies of teaching, training, and learning related to responsible innovation in formal (e.g., classroom) and informal (e.g., museum) environments.

The Journal of Scheduling provides a global forum for the publication of all forms of scheduling research. It is the only peer reviewed journal with broad coverage of the techniques and applications of scheduling that spans several distinct disciplines. Readers facing complex scheduling problems can turn to the journal to find the latest advances in the field. Each issue features new and novel techniques, applications, theoretical issues, and innovative approaches to problems. The journal is designed to assist readers in computer science, discrete mathematics, operational research, engineering, management, artificial intelligence, construction, distribution, manufacturing, transportation, aerospace, and retail and service industries.Officially cited as: J Sched

The Journal of Sport Management encourages the submission of manuscripts in a number of areas as they relate to the management, governance, and consumption of sport such as: organizational theory, behavior, and strategy; sport operations; law and policy; economics, finance, and accounting; marketing, consumer behavior, sponsorship, advertising, and licensing; media, communications, and public relations; sport tourism; facility and event management; and gender and diversity. Studies using quantitative and/or qualitative approaches are welcomed.The Journal of Sport Management publishes research and scholarly review articles; short reports on replications, test development, and data reanalysis (Research Notes); editorials that focus on significant issues pertaining to sport management (Sport Management Perspectives); articles aimed at strengthening the link between sport management theory and sport management practice (From the Field); journal abstracts (Sport Management Digest); book reviews (Off the Press); and news items of interest to professionals in sport management (Management Memos).

Journal of Statistical Computation and Simulation publishes significant and original work in areas of statistics which are related to or dependent upon the computer.Fields covered include computer algorithms related to probability or statistics, studies in statistical inference by means of simulation techniques, and implementation of interactive statistical systems.2009 5-year Impact Factor: 0.517169; 2010 Thomson Reuters, 2009 Journal Citation Reports174; All published research articles in this journal have undergone rigorous peer review, based on initial editor screening and anonymous refereeing by independent expert referees.DisclaimerTaylor & Francis makes every effort to ensure the accuracy of all the information (the 8220;Content8221;) contained in its publications. However, Taylor & Francis and its agents and licensors make no representations or warranties whatsoever as to the accuracy, completeness or suitability for any purpose of the Content and disclaim all such representations and warranties whether express or implied to the maximum extent permitted by law. Any views expressed in this publication are the views of the authors and are not the views of Taylor & Francis.

Journal of Statistical Mechanics: Theory and Experiment (JSTAT) covers all aspects of statistical physics, including experimental work that impacts on the subject.

The Journal of Statistical Planning and Inference offers itself as a multifaceted and all-inclusive bridge between classical aspects of statistics and probability, and the emerging interdisciplinary aspects that have a potential of revolutionizing the subject. While we maintain our traditional strength in statistical inference, design, classical probability, and large sample methods, we also have a far more inclusive and broadened scope to keep up with the new problems that confront us as statisticians, mathematicians, and scientists.We publish high quality articles in all branches of statistics, probability, discrete mathematics, machine learning, and bioinformatics. We also especially welcome well written and up to date review articles on fundamental themes of statistics, probability, machine learning, and general biostatistics. Thoughtful letters to the editors, interesting problems in need of a solution, and short notes carrying an element of elegance or beauty are equally welcome.We want to serve as the broadest international platform for high quality research on every aspect of our field, traditional and cutting edge. The quality and the breadth of our editorial board reflects that singular priority.

Since 1960, IUPAC has made available to chemists everywhere a large amount of important chemical information published in the journal .