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This paper attempts to examine the practical condition of implementing risk‐based approach (RBA) in Chinese financial sectors.

This paper compares the differences between rule‐based approach and risk‐based approach (RBA), and provides different options to financial institutions considering their own circumstances.

This paper finds that capacity constraint is an issue for directly transplanting the RBA performed by developed countries to Chinese financial institutions.

This paper creatively proposes a rule‐based but risk‐oriented AML approach or partial RBA that fits Chinese financial institutions' reality underpinned by Chinese culture, and correspondingly, different assessment methods are presented as well.

The purpose of this paper is to present a fuzzy-rule-based model to classify spare parts inventories considering multiple criteria for better management of maintenance activities to overcome production down situation.

Fuzzy-rule-based approach for multi-criteria decision making is used to classify the spare parts inventories. Total cost is computed for each group considering suitable inventory policies and compared with other existing models.

Fuzzy-rule-based multi-criteria classification model provides better results as compared to aggregate scoring and traditional ABC classification. This model offers the flexibility for inventory management experts to provide their subjective inputs.

The web-based model developed in this paper can be implemented in various industries such as manufacturing, chemical plants, and mining, etc., which deal with large number of spares. This method classifies the spares into three categories A, B and C considering multiple criteria and relationships among those criteria. The framework is flexible enough to add additional criteria and to modify fuzzy-rule-base at any point of time by the decision makers. This model can be easily integrated to any customized Enterprise Resource Planning applications.

The value of this paper is in applying Fuzzy-rule-based approach for Multi-criteria Inventory Classification of spare parts. This rule-based approach considering multiple criteria is not very common in classification of spare parts inventories. Total cost comparison is made to compare the performance of proposed model with the traditional classifications and the result shows that proposed fuzzy-rule-based classification approach performs better than the traditional ABC and gives almost the same cost as aggregate scoring model. Hence, this method is valid and adds a new value to spare parts classification for better management decisions.

The purpose of this paper is to explain the rule‐based and risk‐based anti‐money‐laundering (AML) approach, to demonstrate the implementation problems in carrying out a risk‐based approach (RBA) to AML and finally propose in what way the RBA should be conducted in China.

This paper analyzes the practice of money‐laundering risk management in Chinese AML programs, compares the rule‐based AML approach and the risk‐based AML approach, and discusses the practical condition of carrying out the risk‐based AML approach in China.

Although China has made significant progress on combating money laundering, the practice of money‐laundering risk management in Chinese AML programs is still weak, and the pre‐conditions for fully implementing the RBA in China are yet to be met.

This paper highlights the practical issues preventing Chinese authorities from fully implementing a risk‐based AML approach, and proposes a “rule‐based but risk‐oriented” AML approach (a partial RBA) in the context of Chinese realities.

According to the SEC, the proposed roadmap for adopting principles-based International Financial Reporting Standards (IFRS) is still a priority. The adoption of IFRS will ultimately demand greater emphasis on practitioner judgment (Mintz, 2010). This chapter focuses on the need for building the judgment skills of the practitioner. Our methodology follows a three-step process. We start with accounting standards, reviewing similarities and differences between “rules-based” and “principles-based” standards and conclude that, while applying any standard requires judgment, applying principles-based standards requires more judgment. We then focus on preparer incentives that can influence this requisite judgment. We use the “fraud triangle” to analyze the influence of incentives on judgment under each standards setting approach. Our third and most important step involves equipping practitioners to make judgments in the presence of incentives. We present and discuss a model that considers economic, social (legal), and ethical dimensions for making principled judgments in the presence of incentives and advocate-improved education for accountants in implementing that model.

In this work, the authors propose to harness the advantages of behavioral programming as a new technique for designing rule-based conversational agents.

To examine the study’s hypotheses, the authors perform a first-of-its-kind user study through which the authors examine how potential designers, both expert designers, computationally-oriented designers, and otherwise, leverage behavioral programming (BP) and dialog graphs for designing conversational agents (CAs). The authors also use two standard CA settings common in the literature: designing a CA representative for a user in an online dating service and a non-character player in a role-playing game (RPG).

The study’s results indicate that BP can be successfully utilized by computationally-oriented designers, with or without prior knowledge in CA design, and can facilitate the design of better CAs (i.e. more accurate and more robust). However, to capitalize on these potential advantages, designers may be required to devote more time to the design process and are likely to encounter higher temporal demand levels. These results suggest that BP, which was initially proposed and evaluated in the general context of software design, can constitute a valuable alternative to the classic rule-based CA design technique commonly practiced today.

An important limitation of this study is the relatively small participant pool. While the authors do plan to extend this study in the future, the current coronavirus disease 2019 (COVID-19) situation makes it ever more complex to conduct formal user studies of this kind. It is, however, important to note that despite the low number of participants, many of the results are found to be statistically significant.

The authors plan to continue this line of work and conduct human studies for additional design techniques in other popular agent-based settings. Specifically, the authors seek to explore how people of different backgrounds should design agents for various tasks such as automated negotiation (e.g. how should a person design a representative agent to negotiate on her behalf?) and social choice (e.g. how should a person design a voting bot to represent her in online voting systems?).

People are increasingly interacting with conversational agents in various settings and for a variety of reasons, as the market size of those agents keeps on growing every year. Through a first-of-its-kind human study (N = 41), consisting of both expert designers, computationally-oriented designers, and otherwise, the authors demonstrate a few key advantages and limitations of BP in the realm of conversational agents and propose its consideration as an alternative to the classic dialog graph technique.

This chapter explores the link between virtue and representational faithfulness in making judgments in a principles-based environment. The motivation for the chapter is the impending adoption of International Financial Reporting Standards (IFRS) in the United States and its principles-based approach to accounting. Even in a rules-based system, there are principles that provide a foundation for making decisions about the selection and implementation of accounting standards, financial statement presentation, estimates, and the sufficiency of evidence. A model is presented that reflects these judgments informed by virtue considerations that support substance over form decisions and a true and fair view. Implications for accounting education are discussed including the readiness of faculty to incorporate IFRS into the curriculum.

This article aims to consider the role of the European Union (EU) in the prevention of money laundering and to show that the EU has a lot more to win in this field of policy.

This article is based on a literature study and a thorough analysis of the EU Directives on the prevention of money laundering.

Whereas, the material norms for entities subject to regulation have been harmonised and adjusted to the risk‐based approach at European level, the norms regarding the enforcement instruments have mostly been left to the Member States' legislation. As a result, there exists a “patchwork” of enforcement mechanisms throughout the EU.

This article focuses on the prevention of money laundering on the level of the EU only; no connection is made to the international or to the national level.

This article does not provide a value judgment on the preventive rules at European level as such, but rather it offers an academic perspective on the role of the EU in the prevention of money laundering.

Customer reviews are one important source that contains valuable information for quality evaluation of products or services. Review sentences contain sentiment words that show whether a user’s opinion is positive or negative. When review sentence has mix opinions, having sentiment words of both polarities, it is difficult to conclude whether it is positive or negative opinion. The purpose of this study is to improve the detection of polarity in such situation.

In this research, methods such as part-of-speech tagging, polarity analysis and rules selection are used to identify the polarity. A set of rules called contrast and conditional polarity rules (CCPR) has been created to improve the polarity detection in cases when there is mixture of sentiment words used in contrast and conditional type of review sentences. The experiment is conducted with data sets from three domains, i.e. restaurant, electronic and Tripadvisor.

The experimental result confirms that CCPR rules have higher baseline of the polarity aggression. In restaurant domain, CCPR rules (62.07%) have increased 13.79% compared with the Pol_Agg_MPQA baseline (48.28%) and 13.79% compared with Pol_Agg_Senti baseline (48.28%). In electronic domain, CCPR rule (79.17%) is higher by 12.50% compared with the Pol_Agg_MPQA baseline (66.67%) and 16.67% compared with Pol_Agg_Senti baseline (62.50%). Another one, CCPR rule (70.83%) is higher by 8.33% compared with the Pol_Agg_MPQA baseline (62.50%) and 12.50% compared with Pol_Agg_Senti baseline (58.33%). In conclusion, result of experiment shows promising outcome with improvement in detecting the positivity and negativity of indirect sentence, especially for the case of sentence with indirect polarity.

To address the problem of mix opinions in terms of polarities, this paper presents a rule-based approach to improve the result of identifying positivity and negativity in sentence with indirect polarities.

Digital resources such as smart applications reviews and online feedback information are important sources to seek customers’ feedback and input. This paper aims to help government entities gain insights on the needs and expectations of their customers. Towards this end, we propose an aspect-based sentiment analysis hybrid approach that integrates domain lexicons and rules to analyse the entities smart apps reviews. The proposed model aims to extract the important aspects from the reviews and classify the corresponding sentiments. This approach adopts language processing techniques, rules, and lexicons to address several sentiment analysis challenges, and produce summarized results. According to the reported results, the aspect extraction accuracy improves significantly when the implicit aspects are considered. Also, the integrated classification model outperforms the lexicon-based baseline and the other rules combinations by 5% in terms of Accuracy on average. Also, when using the same dataset, the proposed approach outperforms machine learning approaches that uses support vector machine (SVM). However, using these lexicons and rules as input features to the SVM model has achieved higher accuracy than other SVM models.

This paper aims to compare the CSR strategy, stakeholder engagement and overseas approaches of six leading companies that have large potential environmental and social impacts, influential stakeholders and notable CSR actions.

This is an exploratory survey based on interviews with senior executives from British and Brazilian companies operating in the steel, petroleum and retail sectors, that makes comparisons between and within them.

The British companies interviewed are more rule-based, adopt an implicit CSR approach, react to stakeholders' demands based on moral motives, and focus on environmental issues. The Brazilian companies reviewed in this study adopt an explicit CSR approach, have relational motives to engage with stakeholders, and are more concerned with building a responsible image and narrowing social gaps.

The survey is based on the perceptions of the senior executives interviewed, which may or may not correspond to actual practices. The sample size restricts generalisation of the results, and the specific firms interviewed may not represent the prevailing CSR business strategy in their respective countries.

British companies can learn from the Brazilian experience how to become more innovative in a broader approach to CSR. Brazil should reinforce its legal framework to provide a more systematic and rule-based approach to CSR, close to the UK experience.

The way CSR is conceived and implemented depends on the ethical, socioeconomic, legal and institutional environment of the country in which the firm operates.