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Presents the master production scheduling (MPS) problem of a flexible manufacturing system (FMS). Earliness/tardiness production scheduling and planning (ETPSP) is one of the solutions used to integrate MRP and JIT effectively. Previous researches on ETPSP have only applied to problems of single/parallel machines with earliness and tardiness penalties on a common due date and capacity. Proposes a revised ETPSP for the purpose of developing an MPS that can fit into the FMS environment where a multiple machine capacity on multi‐processes and batch sizes is included. Outlines the application of an enhanced ETPSP method using a genetic algorithm (GA) solution to solve a multi‐product FMS production problem. Shows that the use of the improved ETPSP model can represent a real life FMS environment and that a solution can be effectively and efficiently obtained using the GA approach.

This paper aims to give a brief review on behavioral economics and behavioral finance and discusses some of the previous research on agents' utility functions, applicable risk measures, diversification strategies and portfolio optimization.

The authors also cover related disciplines such as trading rules, contagion and various econometric aspects.

While scholars could first develop theoretical models in behavioral economics and behavioral finance, they subsequently may develop corresponding statistical and econometric models, this finally includes simulation studies to examine whether the estimators or statistics have good power and size. This all helps us to better understand financial and economic decision-making from a descriptive standpoint.

The research paper is original.

In 2001, the US moved to regulate internal control reporting by management and auditors. While some jurisdictions have followed the lead of the US, many others have not. An important question, therefore, is the relevance of internal control to stakeholders. The more specific issue of the benefits of US-style regulation of internal control reporting is also topical. We review studies on the determinants of internal control quality and its economic consequences for stakeholders including investors, creditors, managers, auditors and financial analysts. We extend previous reviews by focusing on US studies published since 2013 as well as all non-US studies investigating IC quality including countries regulating IC disclosure as well as unregulated settings and both developed and developing economies. In doing so, we identify research questions where evidence remains mixed and new directions in which there are research opportunities.

Three main insights arise from our analysis. First, evidence on the economic consequences of internal control quality suggests that the quality of internal control can have a significant effect on decision making by users of financial information. Second, the results of research on the empirical association between ownership structure, certain board characteristics and internal control quality is generally mixed. Empirical evidence concerning the association between audit committee characteristics and internal control quality generally supports a positive and significant association. Finally, while studies in non-US jurisdictions are increasing, opportunities remain to explore the determinants and consequences of internal control in other jurisdictions. Our review provides evidence for policy makers of whether there are benefits from requiring management and auditors to report on internal control over financial reporting.

Incineration has become increasingly important in many large cities around the world because of fast urbanization and population growth. The benefits of energy production and large reduction in the waste volume to landfills also contribute to its growing adaptation for solid waste management for these cities. At the same time, the environmental impact of the pollutant gases emitted from the incineration process is a common concern for various stakeholders which must be properly addressed. To minimize the pollutant gas emission levels, as well as maximize the energy efficiency, it is critically important to optimize the combustion performance of an incinerator freeboard which would require the development of reliable approaches based on computational fluid dynamics (CFD) modeling. A critical task in the CFD modeling of an incinerator furnace requires the specification of waste characteristics along the moving grate as boundary conditions, which is not available in standard CFD packages at present. This study aims to address this gap by developing a numerical incinerator waste bed model.

A one-dimensional Lagrangian model for the incineration waste bed has been developed, which can be coupled to the furnace CFD model. The changes in bed mass due to drying, pyrolysis, devolatilization and char oxidation are all included in the model. The mass and concentration of gases produced in these processes through reactions are also predicted. The one-dimensional unsteady energy equations of solid and gas phases, which account for the furnace radiation, conduction, convection and heat of reactions, are solved by the control volume method.

The Lagrangian model is validated by comparing its prediction with the experimental data in the literature. The predicted waste bed height reduction, temperature profile and gas concentration are in reasonable agreement with the observations.

The simplicity and efficiency of the model makes it ideally suitable to be used for coupling with the computational furnace model to be developed in future (so as to optimize incinerator designs).

Despite the extensive academic interest in social media sentiment for financial fields, multimodal data in the stock market has been neglected. The purpose of this paper is to explore the influence of multimodal social media data on stock performance, and investigate the underlying mechanism of two forms of social media data, i.e. text and pictures.

This research employs panel vector autoregressive models to quantify the effect of the sentiment derived from two modalities in social media, i.e. text information and picture information. Through the models, the authors examine the short-term and long-term associations between social media sentiment and stock performance, measured by three metrics. Specifically, the authors design an enhanced sentiment analysis method, integrating random walk and word embeddings through Global Vectors for Word Representation (GloVe), to construct a domain-specific lexicon and apply it to textual sentiment analysis. Secondly, the authors exploit a deep learning framework based on convolutional neural networks to analyze the sentiment in picture data.

The empirical results derived from vector autoregressive models reveal that both measures of the sentiment extracted from textual information and pictorial information in social media are significant leading indicators of stock performance. Moreover, pictorial information and textual information have similar relationships with stock performance.

To the best of the authors’ knowledge, this is the first study that incorporates multimodal social media data for sentiment analysis, which is valuable in understanding pictures of social media data. The study offers significant implications for researchers and practitioners. This research informs researchers on the attention of multimodal social media data. The study’s findings provide some managerial recommendations, e.g. watching not only words but also pictures in social media.

This paper aims to propose a novel active SLAM framework to realize avoid obstacles and finish the autonomous navigation in indoor environment.

The improved fuzzy optimized Q-Learning (FOQL) algorithm is used to solve the avoidance obstacles problem of the robot in the environment. To reduce the motion deviation of the robot, fractional controller is designed. The localization of the robot is based on FastSLAM algorithm.

Simulation results of avoiding obstacles using traditional Q-learning algorithm, optimized Q-learning algorithm and FOQL algorithm are compared. The simulation results show that the improved FOQL algorithm has a faster learning speed than other two algorithms. To verify the simulation result, the FOQL algorithm is implemented on a NAO robot and the experimental results demonstrate that the improved fuzzy optimized Q-Learning obstacle avoidance algorithm is feasible and effective.

The improved fuzzy optimized Q-Learning (FOQL) algorithm is used to solve the avoidance obstacles problem of the robot in the environment. To reduce the motion deviation of the robot, fractional controller is designed. To verify the simulation result, the FOQL algorithm is implemented on a NAO robot and the experimental results demonstrate that the improved fuzzy optimized Q-Learning obstacle avoidance algorithm is feasible and effective.

Trauma and adverse childhood events are found in the pre‐immigration histories of a cohort of four Chinese Canadian pathological gamblers. The nature of their traumatic experiences, consisting of loss and abandonment, neglect and deprivation, physical and emotional abuse, socioeconomic and political oppression, is elucidated and described. The impact of pre‐immigration trauma and its relationship to the development of pathological gambling post‐immigration are discussed. Upon further corroboration of the existence of pre‐immigration trauma among Chinese and Asian immigrants in future studies, training of counsellors to incorporate an in‐depth pre‐immigration history in the assessment and treatment protocol of immigrants manifesting pathological gambling is recommended.

This research examines the relationship between market power and liquidity creation in the specific context of bank profitability in the Vietnamese banking sector.

The study applies the methodology proposed by Berger and Bouwman (2009) to demonstrate the creation of bank liquidity through a three-step procedure for investigating the relationship between market power and liquidity creation. The three steps include non-fat liquidity (NFLC), fat liquidity (FLC) and system generalized method of moments estimation for panel data.

This study finds that liquidity creation increases when a bank has high market power. Further, highly profitable banks positively impact the market power of banks with regard to liquidity creation, relative to less profitable banks. Moreover, bank size, capital, economic growth and interest rate negatively influence bank liquidity creation, while credit risk positively relates to bank liquidity creation.

Measurements used in this study are based on the works of Berger and Bouwman (2009). There are specific variations, relative to Basel III. In addition, other variables significantly impact bank liquidity creation that have not been considered in the models, and a quadratic model should have been considered to measure market power and bank liquidity creation.

This study suggests that managers should control the liquidity of their banks by supervising vulnerable characteristics that have been mentioned herein and emphasizing improvements in profitability. Further, the government may consider encouraging banks to generate more liquidity by modifying regulations concerned with market power or reinforcing policies about improving the transparent business environment.

This study characterizes an attempt to examine the influence of market power on the liquidity creation of banks in Vietnam, which represents one of the most dynamic systems in Asia, with several varied participating banks. The current study also examines the same within the specific context of the modifying impact of the profitability of banks.

The purpose of this paper is to identify the radio frequency identification (RFID) strategic value attributes (RFIDSVAs) mechanism selections preferences and also integration of RFID tags with technology coordination tools (IRTWTCTs) alternatives ranking performance decisions in supply chain management (SCM). RFID-enabled techno-economic feasibility decisions are enhancing the SC visibility in apparel supply chains (ASCs). The RFIDSVAs mechanism selections have performed significant agility to strategic competitive advantages, namely, inventory visibility, multi-tags ownership transfer within trusted third party, etc.

Fuzzy analytical hierarchy process (FAHP) and FAHP-fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) approaches have been used to evaluate the quantitative assessment of RFIDSVA mechanisms selection decision based on weight priority orders and IRTWTCTs alternatives selection in ASC networks. The comparison of FAHP and FAHP-FTOPSIS approaches to evaluate the integrated framework develop in RFIDSVAs mechanisms and IRTWTCTs alternatives selection decisions in Indian multi-tier ASC networks.

The result found that the FAHP-FTOPSIS approaches have used to prioritizing the RFIDSVA mechanism selection weights and also identify the IRTWTCTs alternatives ranking preferences order in apparel SCM. The comparison between the FAHP and FAHP-FTOPSIS approach to quantitative assessments from RFIDSVA mechanisms and IRTWTCTs alternatives selection decisions, which enable them SC agility potential across multi-tier visibility in ASC networks. ASC stakeholders can be benefited by techno-economic feasibility decisions, RFID-enabled shop floor activities, multi-tags ownerships transfer in SCs and knowledge-based cryptography tags/items separation in SCs.

The research work has considered only five RFIDSVA mechanisms and also three integration of RFIDTWTCTs alternatives in multi-tier ASC. The strategic competitive advantages are achieved by RFID-enabled break-even tags price decisions and also techno-economic feasibility decision by contractual design multi-tier SC stakeholder’s involvements.

The pilot project study explores that the quantitative assessment decision has based on RFID-enable techno-economic feasibility in ASCs. Stakeholders can be benefited by inventory control of the financial losses, reducing the inventory inaccuracies and multi-tags ownership transfer within trusted third-party traceability in ASC networks.

This study explores the RFID-enabled apparel SC process and activities visibility (natural fibre’s fibre producer, fibre dyeing producer, yarn spinning producer, knitting and finishing producer).