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After the Collective Forest Tenure Reform (CFTR) in China, the enthusiasm of farmers for forestry management is stimulated. However, the forest tenure security varies among farmers, making the research conclusions of its impact on forestry management efficiency inconsistent. Based on the survey data of 1,627 households from the collective forest regions in 6 provinces of China in 2017, this paper not only discusses the differences of farmers' forestry management efficiency after the reform, but also further explores the heterogeneous impact of forest tenure security on forestry management efficiency in combination with different forest management types.

This study employed the stochastic frontier production function model to measure the forestry management efficiency of farmers. Then, Tobit models were used to discuss the influencing factors of farmers' forestry management efficiency.

The results demonstrate that the improvement of farmers' forest tenure security can effectively improve forestry management efficiency, but the effect is affected by forest management types. For farmers who manage economic forests and non-timber forests, safe tenure promotes the forestry management efficiency; while for those who manage ecological public welfare forests, tenure security plays an opposite role.

Therefore, satisfying farmers' differentiated demands for forest tenure according to forest management types to improve forest tenure security and further refining supporting policies of collective forestry reform is of great significance to improve the efficiency of farmers' forestry management in collective forest regions.

The majority of existing studies about named entity recognition (NER) concentrate on the prediction enhancement of deep neural network (DNN)-based models themselves, but the issues about the scarcity of training corpus and the difficulty of annotation quality control are not fully solved, especially for Chinese ancient corpora. Therefore, designing a new integrated solution for Chinese historical NER, including automatic entity extraction and man-machine cooperative annotation, is quite valuable for improving the effectiveness of Chinese historical NER and fostering the development of low-resource information extraction.

The research provides a systematic approach for Chinese historical NER with a three-stage framework. In addition to the stage of basic preprocessing, the authors create, retrain and yield a high-performance NER model only using limited labeled resources during the stage of augmented deep active learning (ADAL), which entails three steps—DNN-based NER modeling, hybrid pool-based sampling (HPS) based on the active learning (AL), and NER-oriented data augmentation (DA). ADAL is thought to have the capacity to maintain the performance of DNN as high as possible under the few-shot constraint. Then, to realize machine-aided quality control in crowdsourcing settings, the authors design a stage of globally-optimized automatic label consolidation (GALC). The core of GALC is a newly-designed label consolidation model called simulated annealing-based automatic label aggregation (“SA-ALC”), which incorporates the factors of worker reliability and global label estimation. The model can assure the annotation quality of those data from a crowdsourcing annotation system.

Extensive experiments on two types of Chinese classical historical datasets show that the authors’ solution can effectively reduce the corpus dependency of a DNN-based NER model and alleviate the problem of label quality. Moreover, the results also show the superior performance of the authors’ pipeline approaches (i.e. HPS + DA and SA-ALC) compared to equivalent baselines in each stage.

The study sheds new light on the automatic extraction of Chinese historical entities in an all-technological-process integration. The solution is helpful to effectively reducing the annotation cost and controlling the labeling quality for the NER task. It can be further applied to similar tasks of information extraction and other low-resource fields in theoretical and practical ways.

The purpose of this paper is to examine the failures of business intelligence (BI) implementations and to understand why they fail as well as what action can be taken to ensure implementation success.

The paper is based on a literature review of academic journals and case studies relating to BI, and the success and failure of the implementation of such projects. It focuses on four areas of BI projects to measure success: return on investment, non-concrete measures, project management measures and user satisfaction. The literature provides insights into what factors contribute to the success of a BI implementation and what factors contribute to the failure. Once the failures can be ascertained, a strategic approach to remedying the failure is discussed.

Implementation failure specifically relating to BI is a rarely discussed topic. This paper provides an understanding of why BI implementations fail and how organisations can ensure, prior to implementing such a solution, the considerations that need to be made to ensure that success is achieved from a technological, organisational and process perspective.

The paper uses empirical evidence from the literature to provide an understanding of why BI implementations fail. The factors contributing to BI failure are examined along with insights into how to succeed with a BI implementation.

Vertical electrical sounding (VES) and Rayleigh wave exploration are widely used in the exploration of near-surface structure, but both have limitations. This study aims to make full use of the advantages of the two methods, reduce the multiple solutions of single inversion and improve the accuracy of the inversion. Thus, a nonlinear joint inversion method of VES and Rayleigh wave exploration based on improved differential evolution (DE) algorithm was proposed.

Based on the DE algorithm, a new initialization strategy was proposed. Then, taking AK-type with high-velocity interlayer model and HA-type with low-velocity interlayer model near the surface as examples, the inversion results of different methods were compared and analyzed. Then, the proposed method was applied to the field data in Chengde, Hebei Province, China. The stratum structure was accurately depicted and verified by drilling.

The synthetic data and field data results showed that the joint inversion of VES and Rayleigh wave data based on the improved DE algorithm can effectively improve the interpretation accuracy of the single-method inversion and had strong stability and large generalizable ability in near-surface engineering problems.

A joint inversion method of VES and Rayleigh wave data based on improved DE algorithm is proposed, which can improve the accuracy of single-method inversion.

The purpose of this paper is to explore the complexities in dashboard design process.

The authors chose case study research, following Benbasat et al. (2002) who argued that it is suitable for information system research, as researchers could perform the study in the organisation as a natural setting. As a result, the authors could learn and generate insights from practice. Another reason was mainly as the phenomenon being studied cannot be taken away from its context (Yin, 2003). In addition, through case study, the authors aim to achieve a deeper understanding and richer descriptions on the subject of research in a “real-world context” (Yin, 2012). In addition, it aims to understand the intricacy of the processes going on in the organisation by focusing more towards organisational rather than the technological issues (Benbasat et al., 1987).

Through research, the authors highlighted that it is important to align the dashboard design with the organisation’s visions and goals. This creates a more persuasive rationale for adoption amongst the users, as they could use the dashboard as a means to assist them in achieving the vision and goals of the organisation. More importantly, the analysis clearly indicates the need to consider the creation of a dashboard as a holistic exercise. The intricate processes of designing a dashboard are often underestimated. Instead of focusing into a specific aspect (such as user interface or functionality) of designing dashboards, the authors should look into the multi-faceted aspects in designing an effective dashboard.

This paper articulates the findings from a single case study. However, arguably, the results of this study are transferable to other entities responsible for designing business intelligence (BI) and business analytics dashboards. Research on dashboard design and the use of design thinking across different type organisations is currently ongoing to allow for cross-case analyses.

The study has determined that interdisciplinary and cross-functional group communications play a significant role in designing a dashboard. The ability to collaborate with “data owners”, would be dashboard users, managers of the technical infrastructure, and process owners leads to a workable and effective dashboard. In this sense, design thinking could be used and/or regarded as a holistic, creative and solutions-oriented framework.

With an increasing interest on BI and business analytics, dashboards have an increasingly pivotal role in providing a summary of data for business users. The literature review shows in designing a dashboard; there is much emphasis on the graphical user interface and in providing features and functionalities for the dashboards. This paper presents a case study outlining the key considerations of a team in charge of business analytics and dashboard creations for a university. Through the case study analysis, the authors explore the key aspects that influence a dashboard design and analyse the design processes using the concept of design thinking as the theoretical framework.

The purpose of this paper is to study the advance selling strategies for oligopolists when considering the product diffusion effect.

The authors consider a market that composes of two competitive sellers who are different in their reputation. The two firms sell the same product in the market over two periods (i.e. the advance selling season and the regular selling season). Due to the effect of product diffusion, the demand of each firm in the regular selling season is dependent on the two firms’ advance demands.

For the firm with lower reputation, it is beneficial to decrease the advance selling price with the diffusion effect caused by its advance demand. For the firm with higher reputation, it is also beneficial to decrease the advance selling price with the diffusion effect caused by its advance demand if the consumers’ enthusiasm for the product in regular selling season is high enough; otherwise it should not decrease his advance selling price since this practice cannot greatly increase his demand.

The obtained results can provide operational managers in reality with valuable suggestions in making advance selling decisions.

The paper is among the first to investigate the impact of product diffusion effect on a firm’s advance selling strategy in a competitive setting.

The purpose of this paper is to summarize the progress in grey system research during 2000-2015, so as to present some important new concepts, models, methods and a new framework of grey system theory.

The new thinking, new models and new methods of grey system theory and their applications are presented in this paper. It includes algorithm rules of grey numbers based on the “kernel” and the degree of greyness of grey numbers, the concept of general grey numbers, the synthesis axiom of degree of greyness of grey numbers and their operations; the general form of buffer operators of grey sequence operators; the four basic models of grey model GM(1,1), such as even GM, original difference GM, even difference GM, discrete GM and the suitable sequence type of each basic model, and suitable range of most used grey forecasting models; the similarity degree of grey incidences, the closeness degree of grey incidences and the three-dimensional absolute degree of grey incidence of grey incidence analysis models; the grey cluster model based on center-point and end-point mixed triangular whitenization functions; the multi-attribute intelligent grey target decision model, the two stages decision model with grey synthetic measure of grey decision models; grey game models, grey input-output models of grey combined models; and the problems of robust stability for grey stochastic time-delay systems of neutral type, distributed-delay type and neutral distributed-delay type of grey control, etc. And the new framework of grey system theory is given as well.

The problems which remain for further studying are discussed at the end of each section. The reader could know the general picture of research and developing trend of grey system theory from this paper.

A lot of successful practical applications of the new models to solve various problems have been found in many different areas of natural science, social science and engineering, including spaceflight, civil aviation, information, metallurgy, machinery, petroleum, chemical industry, electrical power, electronics, light industries, energy resources, transportation, medicine, health, agriculture, forestry, geography, hydrology, seismology, meteorology, environment protection, architecture, behavioral science, management science, law, education, military science, etc. These practical applications have brought forward definite and noticeable social and economic benefits. It demonstrates a wide range of applicability of grey system theory, especially in the situation where the available information is incomplete and the collected data are inaccurate.

The reader is given a general picture of grey systems theory as a new model system and a new framework for studying problems where partial information is known; especially for uncertain systems with few data points and poor information. The problems remaining for further studying are identified at the end of each section.

The four major Subject Repositories (SRs), arXiv, Research Papers in Economics (RePEc), Social Science Research Network (SSRN) and PubMed Central (PMC), are all important within their disciplines but no previous study has systematically compared how often they are cited in academic publications. In response, the purpose of this paper is to report an analysis of citations to SRs from Scopus publications, 2000-2013.

Scopus searches were used to count the number of documents citing the four SRs in each year. A random sample of 384 documents citing the four SRs was then visited to investigate the nature of the citations.

Each SR was most cited within its own subject area but attracted substantial citations from other subject areas, suggesting that they are open to interdisciplinary uses. The proportion of documents citing each SR is continuing to increase rapidly, and the SRs all seem to attract substantial numbers of citations from more than one discipline.

Scopus does not cover all publications, and most citations to documents found in the four SRs presumably cite the published version, when one exists, rather than the repository version.

SRs are continuing to grow and do not seem to be threatened by institutional repositories and so research managers should encourage their continued use within their core disciplines, including for research that aims at an audience in other disciplines.

This is the first simultaneous analysis of Scopus citations to the four most popular SRs.

The purpose of this paper is to summarize the advances in grey system theory research and various application achievements in science and engineering. At the same time, it commemorates the 40th anniversary of the birth of grey system theory and the 10th anniversary of Grey Systems–Theory and Application.

Firstly, the innovations of theoretical research in grey system theory were summarized and some of the widely recognized new results are briefly described. By searching and combing the research results of grey system theory in China national knowledge infrastructure (CNKI) database and Web of Science by Institute for Scientific Information (ISI), this paper shows the rapid development trend of grey system theory in the past 40 years, and the successful applications of grey system theory in the fields of social sciences, natural sciences and engineering technologies.

More than 227 thousands literature were found by input 10 phrases such as grey system, grey number and sequence operator etc. in CNKI database. After entering the new century, the number of grey system papers included in CNKI database is increasing rapidly. Since 2008, more than 10 thousands papers have been included per year and more than 15 thousands papers have been included per year since 2014. Grey system method and model are widely used in physics, chemistry, biology and other fields of natural science, as well as transportation, electric power, machinery and other fields of engineering technology, and a large number of valuable results have been achieved.

It can be seen that the grey system theory plays an important role in promoting China’s scientific and technological progress, innovation and development and high-level talent training from tens of thousands of literatures marked with important national science and technology projects and a large number of grey system literatures published by China’s double first-class universities and double first-class discipline construction universities.

Both innovations of theoretical research and practical application play important role in the growth of new theory. The innovations of theoretical research provide methods and tools for practical application, which is conducive to improve application efficiency and broaden application fields. A large number of practical applications needs have become the source of theoretical innovation and the solid background for the birth of theoretical innovation achievements.