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Project scheduling plays an essential role in the implementation of a project due to the limitation of resources in practical projects. However, the existing research tend to focus on finding suitable algorithms to solve various scheduling problems and fail to find the potential scheduling rules in these optimal or near-optimal solutions, that is, the possible intrinsic relationships between attributes related to the scheduling of activity sequences. Data mining (DM) is used to analyze and interpret data to obtain valuable information stored in large-scale data. The goal of this paper is to use DM to discover scheduling concepts and obtain a set of rules that approximate effective solutions to resource-constrained project scheduling problems. These rules do not require any search and simulation, which have extremely low time complexity and support real-time decision-making to improve planning/scheduling.

The resource-constrained project scheduling problem can be described as scheduling a group of interrelated activities to optimize the project completion time and other objectives while satisfying the activity priority relationship and resource constraints. This paper proposes a new approach to solve the resource-constrained project scheduling problem by combining DM technology and the genetic algorithm (GA). More specifically, the GA is used to generate various optimal project scheduling schemes, after that C4.5 decision tree (DT) is adopted to obtain valuable knowledge from these schemes for further predicting and solving new scheduling problems.

In this study, the authors use GA and DM technology to analyze and extract knowledge from a large number of scheduling schemes, and determine the scheduling rule set to minimize the completion time. In order to verify the application effect of the proposed DT classification model, the J30, J60 and J120 datasets in PSPLIB are used to test the validity of the scheduling rules. The results show that DT can readily duplicate the excellent performance of GA for scheduling problems of different scales. In addition, the DT prediction model developed in this study is applied to a high-rise residential project consisting of 117 activities. The results show that compared with the completion time obtained by GA, the DT model can realize rapid adjustment of project scheduling problem to deal with the dynamic environment interference. In a word, the data-based approach is feasible, practical and effective. It not only captures the knowledge contained in the known optimal scheduling schemes, but also helps to provide a flexible scheduling decision-making approach for project implementation.

This paper proposes a novel knowledge-based project scheduling approach. In previous studies, intelligent optimization algorithm is often used to solve the project scheduling problem. However, although these intelligent optimization algorithms can generate a set of effective solutions for problem instances, they are unable to explain the process of decision-making, nor can they identify the characteristics of good scheduling decisions generated by the optimization process. Moreover, their calculation is slow and complex, which is not suitable for planning and scheduling complex projects. In this study, the set of effective solutions of problem instances is taken as the training dataset of DM algorithm, and the extracted scheduling rules can provide the prediction and solution of new scheduling problems. The proposed method focuses on identifying the key parameters of a specific dynamic scheduling environment, which can not only reproduces the scheduling performance of the original algorithm well, but also has the ability to make decisions quickly under the dynamic interference construction scenario. It is helpful for project managers to implement quick decisions in response to construction emergencies, which is of great practical significance for improving the flexibility and efficiency of construction projects.

The purpose of this paper is to examine the alternative accounts produced by Green Earth Volunteers (GEV), a Chinese environmental non-governmental organisation, over a 10-year period in the context of their campaign to create visibilities about hydroelectric dam projects along the Chang Jiang.

Drawing on conceptions of the human–nature relationship, including those evident in ancient Chinese philosophy and mythology, and the Chinese way of viewing and resolving conflict, this paper offers an interpretive analysis of the alternative accounts of GEV in terms of their form and content.

In terms of their content, the alternative accounts reflect elements of interrelated thinking, being underpinned by a recognition of the relationship between humans and nature, which is evident in Confucianism, Taoism and ancient Chinese mythology. The strategies adopted by GEV are a non-confrontational but feasible way to promote their ecological beliefs in the Chinese context.

The study suggests that social and environmental accounting (SEA) in developing countries is steeped in local cultural and philosophical traditions that need to be considered and incorporated into the design of alternative accounts.

The study contributes to the very limited literature that offers qualitative analyses of SEA in developing countries.

This paper breaks through the limitations of the research on bullwhip effect in the traditional supply chain, extends the research perspective to digital supply chain and discusses the weakening effect of digital supply chain on bullwhip effect by comparing the overall performance of the two.

This paper starts with the weakening mechanism of supply chain digitization on bullwhip effect, builds bullwhip effect models of traditional supply chain and digital supply chain, respectively, simulates the influence of supply chain digitization transformation on bullwhip effect by using Matlab software and analyzes the causes of bullwhip effect in supply chain led by T company and the digitization process.

Firstly, digitization can reduce bullwhip effect in multi-level supply chain by reducing information feedback deviation. Second, digital transformation is conducive to improving the overall performance of the supply chain. Third, government incentives can promote the digital transformation of supply chain and inhibit bullwhip effect.

Although the study considers the heterogeneous subject -- the government's incentive effect on digital transformation and information sharing – it does not include the influence of the end node in the supply chain, that is the consumer. In addition, this paper only analyzes and discusses the bullwhip effect on the amplification of demand, without considering the situation that the market contraction will lead to the reduction of demand.

This paper considers the distortion degree and delay degree of information feedback, carries out quantitative analysis of bullwhip effect, builds the bullwhip effect model of traditional supply chain and digital supply chain, uses Matlab software to analyze the difference of the influence of supply chain digital transformation on bullwhip effect suppression and puts forward the corresponding control strategy.

The research shows that digital transformation can reduce the bullwhip effect in multi-layer supply chain by reducing the information feedback deviation, which is conducive to improving the overall supply chain performance, and government support can accelerate the digital transformation of supply chain to a certain extent.

First, break through the limitations of traditional supply chain research, expand the research perspective to digital supply chain and discuss the weakening effect of digital supply chain on bullwhip effect by comparing the overall performance of the two. Second, quantify the bullwhip effect through information feedback bias and provide an analysis method for the weakening of the bullwhip effect. Third, the driving role of the government in the digital transformation of the supply chain is considered in the study, so that the model is more close to the actual situation of enterprise operation.

The purpose of this paper is to obtain a more accurate fatigue life of structures by introducing the surface roughness into fatigue life prediction model.

Based on the fatigue life prediction model with surface roughness correction, the shock absorber cylinder is taken as an example to verify the feasibility of the improved method. Based on the load of the shock absorber cylinder during driving, fatigue experiments are performed under longitudinal and lateral forces, respectively. Then, the fatigue life predicted by the modified model is compared with that predicted by the traditional model.

By comparing with the test results, considering the influence of mean stress, the Manson method is more accurate in life prediction. Then, the modified Manson-Coffin and Manson method with surface roughness is more accurate in life prediction under longitudinal force and lateral forces, respectively. This verifies the feasibility of the improved method with the surface roughness.

The research on the influence of surface roughness on fatigue life can lay the technical foundation for the life prediction of products and have great significance to the quality evaluation of products.

This paper examines the effect of political connections (PCs) on firms' profitability and market value in the Egyptian market after the uprising of 2013.

An empirical study is conducted based on 284 firm-year observations for non-financial listed firms on the EGX100 during the period of 2014–2017. To test the study’s hypothesis, two independent sample t-test, Pearson correlation analysis and ordinary least square (OLS) regressions are conducted.

The results suggest that PCs are common across all industries in Egypt, the PCs through top officers do not improve firm's profitability; however, it has a positive effect on firms' market value. Further, PCs through business owners improve neither profitability nor the market value. Finally, the results suggest that PCs through government ownership have a positive effect on both firms' profitability and market value.

The study’s finding encourages policymakers and regulators in emerging markets, e.g. Egypt, to develop stricter laws, policies and regulatory initiatives to restrain the potential conflict of interest in the politically connected firms.

To the best of the authors' knowledge, this study is one of the first to examine the relationship between PCs and both firms’ profitability and market value in Egypt.

The aim of the paper is to shed light on the use of chitosans and chitooligosaccharides as biopreservatives in various foods animal. Foods of animal and aquatic origin (milk, meat, fish, eggs, sea foods, etc) become contaminated with a wide range of microorganisms (bacteria, molds and yeasts) during harvesting, transporting, processing, handling and storage operations. Due to the perishable nature of these foods, their preservation is of utmost importance. Though many synthetic chemicals are available, yet their use is quite restricted due to their hazardous effects on human health.

Within the domain of food industry, traditionally chitosan is used for biopreservation of foods, which is well known for its nutritional and medicinal properties in human nutrition. However, chitooligosaccharides also possess a number of nutraceutical and health promoting properties in addition to their preservative effect and shelf-life extension of foods. In this study, the comparative effects of both chitosan and chitooligosaccharides on preservation of foods of animal and aquatic origin have been summarized.

Though chitosan has been extensively studied in various foods, yet the use of chitooligosaccharides has been relatively less explored. Chitooligosaccharides are bioactive molecules generated from chitosan and have several advantages over the traditional use of chitosan both in food products and on human health. But unfortunately, little or no literature is available on the use of chitooligosaccharides for preservation of some of the foods of animal origin. Notable examples in this category include cheese, beef, pork, chicken, fish, sea foods, etc.

This paper focuses on the effects of chitosans and chitooligosaccharides on the processing and storage quality of foods of animal and aquatic origin, which offers a promising future for the development of functional foods.

The purpose of this study is to build a personalized learning intervention system, which can support students' personalized learning, improve teachers' teaching efficiency and students' learning effect.

The research proposes a personalized learning intervention method based on a collaborative filtering algorithm and knowledge map. The application of knowledge map makes learning content organized, and the use of collaborative filtering algorithm makes it possible to provide personalized learning recommendations for students. This personalized learning intervention system can monitor students' learning development and achieve the combination of personalized and efficiency. For the study, 152 seventh graders were assigned to a control group and an experimental group. Traditional learning intervention was used in the control group, and individualized learning intervention was used in the experimental group.

SPSS was used for data organization and analysis. The effectiveness of the personalized learning intervention system is verified by quasi-experimental research, and the influence of the system on students' learning effect is discussed. The result found that personalized learning interventions were more effective than traditional approaches in improving students’ achievement. However, for students of different learning levels, personalized learning intervention system has different effects on learning confidence and learning anxiety.

The personalized learning intervention system based on the collaborative filtering algorithm and knowledge map is effective in improving learning effect. And, it also has a certain influence on students' psychology.

The purpose of this paper is to empirically examine whether corporate insiders extract information from activity of outsiders, specifically the short sellers.

Using portfolio approach and Fama-MacBeth regressions, this study examines the relation between short interest and subsequent insider trading activities.

The following results are reported. First, there is a strong inverse relation between short selling and subsequent insider trading, which is partially due to common private information and same target firm characteristics. Second, insiders extract information from shorts. This information extraction effect is more pronounced for firms whose insiders have stronger incentives to extract shorts information (insider purchases, higher short sale constraints, and better information environments). Third, during the September 2008 shorting ban, the information extraction affect disappeared among the large banned firms, whose shorting activities were distorted.

The findings contradict the of-cited accusations corporate executives hold against short sellers. Instead, corporate insiders appear to trade in the same direction as suggested by shorting activities.

Among the vocal critics of short sellers are corporate insiders, who allege that short sellers beat down their stock prices. Many corporations even engage in stock repurchases to show confidence that the stock will perform well going forward despite the short sellers’ actions. This paper’s analysis on their personal portfolios suggests the other way around.

By focusing on how corporate insider trading is related to shorts information, this paper sheds new light on whether corporate decisions convey the true information the corporate insiders possess.

In spite of the government’s support for small-scale rice farmers in rural areas of Thailand, several problems still affect their production and marketing performance. This study aims to assess a rice production community enterprise (RPCE) through an in-depth investigation of its problems and capabilities; and formulate internal strategic guidelines for enterprise development.

This study used a qualitative approach through in-depth interviews with the community enterprise leader and committee members, and focus group discussion with eight farmer-members, purposively selected in Chachoengsao, Thailand. Data were transcribed, sorted and organised to determine themes and patterns. Strengths, weaknesses, opportunities and threats (SWOT) and threats, opportunities, weaknesses and strengths (TOWS) matrix situational analyses were done to develop strategic options. Strategic guidelines were formulated through a final deliberation with all members to ensure strategies aligned with the enterprise’s goals and objectives.

The results have identified three main problem categories encountered by the community enterprise in the areas of membership and labour; production and milling operations; and product design and marketing. The enterprise’s main strengths and opportunities include its product certifications and support from external organisations. Strategic points were developed, and policy support programmes are recommended for capacity building and product development as most problems identified relate to these aspects.

The utility of this study is its focus on an RPCE. The findings will help policymakers and concerned government agencies implement better programmes and policies to develop RPCEs. Furthermore, this study will be a source for future qualitative literature that will provide helpful information to other studies aiming to develop other types of community enterprises (CEs).