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Money laundering (ML) is a major criminal offence stemming from unethical practices by personnel on the ground at Chattogram Port, an important import and export facility in Bangladesh. Because money can be more easily laundered through imports, it is necessary to investigate the dubious process in this sector. This study aims to identify the items most regularly used for easy ML and the factors contributing to their vulnerability.

This research uses a qualitative approach and analyses information from primary sources. Data is obtained from customs officials, port authority personnel, importers and customs brokers through semi-structured questionnaires. Although there are many techniques for ML, this study only found three most overwhelming: under-invoicing, over-invoicing and misdeclaration. A few case studies have been used based on newspaper reports and the internet to triangulate the qualitative data.

Four import items – food products, garments, capital machinery and chemicals – have a higher risk of ML. This study also revealed that money launderers prefer under-invoicing food and garment items. Misdeclaration is more commonly associated with capital machinery and chemical items. Over-invoicing, on the other hand, is only prevalent in government purchases. The port authorities need to pay particular attention to these issues.

As ML is an ongoing activity that changes over time, the findings of this research are circumscribed by the data collected at a single point in time. Additionally, this research did not consider alternative laundering methods.

The research results can provide a basis for creating effective anti-money laundering (AML) strategies to assist with sustainable economic growth.

Developing effective AML measures can help combat corruption and establish good governance in the country and support human well-being.

This paper presents original research findings based on technical analysis. The Chattogram Port Authority and the National Board of Revenue have accepted and used the main findings in a collaborative action plan to tackle ML. The Bangladesh Bank, the country’s central bank, has also incorporated the necessary guidelines and regulations into the Money Laundering Prevention Act, 2012.

Rebar is the prime component of reinforced concrete structures, and rebar monitoring is a time-consuming and technical job. With the emergence of the fourth industrial revolution, the construction industry practices have evolved toward digitalization. Still, hesitation remains among stakeholders toward the adoption of advanced technologies and one of the significant reasons is the unavailability of knowledge frameworks and implementation guidelines. This study aims to investigate technical factors impacting automated monitoring of rebar for the understanding, confidence gain and effective implementation by construction industry stakeholders.

A structured study pipeline has been adopted, which includes a systematic literature collection, semistructured interviews, pilot survey, questionnaire survey and statistical analyses via merging two techniques, i.e. structural equation modeling and relative importance index.

The achieved model highlights “digital images” and “scanning” as two main categories being adopted for automated rebar monitoring. Moreover, “external influence”, “data-capturing”, “image quality”, and “environment” have been identified as the main factors under “digital images”. On the other hand, “object distance”, “rebar shape”, “occlusion” and “rebar spacing” have been highlighted as the main contributing factors under “scanning”.

The study provides a base guideline for the construction industry stakeholders to gain confidence in automated monitoring of rebar via vision-based technologies and effective implementation of the progress-monitoring processes. This study, via structured data collection, performed qualitative and quantitative analyses to investigate technical factors for effective rebar monitoring via vision-based technologies in the form of a mathematical model.

This study aims to investigate Bangladesh’s e-commerce regulations in light of the growing criticism that they are insufficient to curb predicate crimes like fraud and money laundering in the online marketplace.

This study used the exploratory design to examine the latest ministerial directives and laws governing e-commerce in Bangladesh to determine why they cannot prevent fraudulent activities in this promising sector and identify potential solutions.

Bangladesh’s regulatory responses to e-commerce fraud prevention and detection are reactive and inadequate. Regulators are unwilling and unable to enforce available legal provisions for various reasons, including a lack of knowledge and coordination among the agencies.

This paper focuses solely on the legal and regulatory framework in place to combat e-commerce fraud. Other critical issues, such as consumer rights, privacy and data protection in e-commerce, are not addressed.

The findings of this study will assist policymakers in revising current regulatory approaches to e-commerce to protect this sector from criminal abuse.

This study looked into the possibility of using a proactive risk-based approach in the e-commerce sector, similar to what the Bangladesh Financial Intelligence Unit does in the financial sector.

Digital twin (DT) and building information modeling (BIM) are interconnected in some ways. However, there has been some misconception about how DT differs from BIM. As a result, industry professionals reject DT even in BIM-based construction projects due to reluctance to innovate. Furthermore, researchers have repeatedly developed tools and techniques with the same goals using DT and BIM to assist practitioners in construction projects. Therefore, this study aims to assist industry professionals and researchers in understanding the relationship between DT and BIM and synthesize existing works on DT and BIM.

A systematic review was conducted on published articles related to DT and BIM. A total record of 54 journal articles were identified and analyzed.

The analysis of the selected journal articles revealed four types of relationships between DT and BIM: BIM is a subset of DT, DT is a subset of BIM, BIM is DT, and no relationship between BIM and DT. The existing research on DT and BIM in construction projects targets improvements in five areas: planning, design, construction, operations and maintenance, and decommissioning. In addition, several areas have emerged, such as developing geo-referencing approaches for infrastructure projects, applying the proposed methodology to other construction geometries and creating 3D visualization using color schemes.

This study contributed to the existing body of knowledge by overviewing existing research related to DT and BIM in construction projects. Also, it reveals research gaps in the body of knowledge to point out directions for future research.

The application of integrated project delivery (IPD) in conjunction with building information modeling (BIM) and Lean Construction (LC) as the efficient method for improving collaboration and delivering construction projects has been acknowledged by construction academics and professionals. Once organizations have fully embraced BIM, IPD and LC integration, a measurement tool such as a maturity model (MM) for benchmarking their progress and setting realistic goals for continuous improvement will be required. In the context of MMs literature, however, no comprehensive analysis of these three construction management methods has been published to reveal the current trends and common themes in which the models have approached each other.

Therefore, this study integrates systematic literature review (SLR) and thematic analysis techniques to review and categorize the related MMs; the key themes in which the interrelationship between BIM, IPD and LC MMs has been discussed and conceptualized in the attributes; the shared characteristics of the existing BIM, IPD and LC MMs, as well as their strengths and limitations. The Preferred Reporting Items for Systematic Reviews (PRISMA) method has been used as the primary procedure for article screening and reviewing published papers between 2007 and 2022.

Despite the growth of BIM, IPD and LC integration publications and acknowledgment in the literature, no MM has been established that holistically measures BIM, IPD and LC integration in an organization. This study identifies five interrelated and overlapping themes indicative of the collaboration of BIM, IPD and LC in existing MMs' structure, including customer satisfaction, waste minimization, Lean practices and cultural and legal aspects. Furthermore, the MMs' common characteristics, strengths and limitations are evaluated to provide a foundation for developing future BIM, IPD and LC-related MMs.

This paper examines the current status of research and the knowledge gaps around BIM, IPD and LC MMs. In addition, the highlighted major themes serve as a foundation for academics who intend to develop integrated BIM, IPD, and LC MMs. This will enable researchers to build upon these themes and establish a comprehensive list of maturity attributes fulfilling the BIM, IPD and LC requirements and principles. In addition, the MMs' BIM, IPD and LC compatibility themes, which go beyond themes' intended characteristics in silos, increase industry practitioners' awareness of the underlying factors of BIM, IPD and LC integration.

This review article is the first of a kind to analyze the interaction of IPD, BIM and LC in the context of MMs in current AEC literature. This study concludes that BIM, IPD and LC share several joint cornerstones according to the existing MMs.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing studies rarely take a perspective of educational technology application to evaluate the application of chatbots to educational contexts. This study aims to bridge the research gap by taking an educational perspective to review the existing literature on artificial intelligence chatbots.

This study combines bibliometric analysis and citation network analysis: a bibliometric analysis through visualization of keyword, authors, organizations and countries and a citation network analysis based on literature clustering.

Educational applications of chatbots are still rising in post-COVID-19 learning environments. Popular research issues on this topic include technological advancements, students’ perception of chatbots and effectiveness of chatbots in different educational contexts. Originating from similar technological and theoretical foundations, chatbots are primarily applied to language education, educational services (such as information counseling and automated grading), health-care education and medical training. Diversifying application contexts demonstrate specific purposes for using chatbots in education but are confronted with some common challenges. Multi-faceted factors can influence the effectiveness and acceptance of chatbots in education. This study provides an extended framework to facilitate extending artificial intelligence chatbot applications in education.

The authors have to acknowledge that this study is subjected to some limitations. First, the literature search was based on the core collection on Web of Science, which did not include some existing studies. Second, this bibliometric analysis only included studies published in English. Third, due to the limitation in technological expertise, the authors could not comprehensively interpret the implications of some studies reporting technological advancements. However, this study intended to establish its research significance by summarizing and evaluating the effectiveness of artificial intelligence chatbots from an educational perspective.

This study identifies the publication trends of artificial intelligence chatbots in educational contexts. It bridges the research gap caused by previous neglection of treating educational contexts as an interconnected whole which can demonstrate its characteristics. It identifies the major application contexts of artificial intelligence chatbots in education and encouraged further extending of applications. It also proposes an extended framework to consider that covers three critical components of technological integration in education when future researchers and instructors apply artificial intelligence chatbots to new educational contexts.

This study aims to evaluate the advantages and disadvantages of auditor mandatory suspicious activity reporting versus the exercise of professional judgement in the anti-money laundering regimes of the UK and the USA.

The research draws upon the following sources. Firstly, statistics provided by the UK National Crime Agency, 2019 (NCA) regarding suspicious activity report (SAR) filing rates. Secondly, anti-money laundering legislation in the USA and UK. Thirdly, statements made in the political domain in the USA, particularly those which raised constitutional concerns during the progress of the Patriot Act 2001. Finally, statements and recommendations by a UK Parliamentary Commission enquiring into the effectiveness of the suspicious activity reporting regime.

The UK reporting regime does not accommodate professional judgement, resulting in the filing of SARs with limited intelligence value. This contrasts with discretionary reporting in the USA: voluntary reporting guides and influences auditor behaviour rather than mandating it. Defensive filing by UK auditors (defence to anti-money launderings [DAMLs]) has increased in recent years but the number of SARs filed has declined.

The study evaluates auditor behavioural responses to legislative regimes which mandate or alternatively accommodate discretion in the reporting suspicion of money laundering. Consideration of constitutional and judicial activism in this context is a novel contribution to the literature. For its theoretical framework the study uses Foucault’s concept of discipline of the self to evaluate auditor behaviour under both regimes.

Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team interacts when making BMI decisions. The paper also investigates how group biases and board members’ risk willingness affect this process.

Empirical data were collected through 26 in-depth interviews with German managing directors from 13 companies in four industries (mobility, manufacturing, healthcare and energy) to explore three research questions: (1) What group effects are prevalent in BMI group decision-making? (2) What are the key characteristics of BMI group decisions? And (3) what are the potential relationships between BMI group decision-making and managers' risk willingness? A thematic analysis based on Gioia's guidelines was conducted to identify themes in the comprehensive dataset.

First, the results show four typical group biases in BMI group decisions: Groupthink, social influence, hidden profile and group polarization. Findings show that the hidden profile paradigm and groupthink theory are essential in the context of BMI decisions. Second, we developed a BMI decision matrix, including the following key characteristics of BMI group decision-making managerial cohesion, conflict readiness and information- and emotion-based decision behavior. Third, in contrast to previous literature, we found that individual risk aversion can improve the quality of BMI decisions.

This paper provides managers with an opportunity to become aware of group biases that may impede their strategic BMI decisions. Specifically, it points out that managers should consider the key cognitive constraints due to their interactions when making BMI decisions. This work also highlights the importance of risk-averse decision-makers on boards.

This qualitative study contributes to the literature on decision-making by revealing key cognitive group biases in strategic decision-making. This study also enriches the behavioral science research stream of the BMI literature by attributing a critical influence on the quality of BMI decisions to managers' group interactions. In addition, this article provides new perspectives on managers' risk aversion in strategic decision-making.

The author employed a five-step approach: Data (e.g., qualitative primary and secondary data) collection (about a major project at the examined organisation), Critical thinking (in order to determine the dilemma), Setting learning objectives (e.g., with respect to the Bloom's taxonomy), Testing (in order to confirm the teaching plan) (e.g., with research assistants and doctoral candidates), and Ensuring clarity (e.g., especially for the case narrative).

The site manager at a UNESCO World Heritage Site by the name Ephesus in Türkiye (Turkey) was considering who would update the site management plan. UNESCO was regularly asking for updates. Would site management outsource the management plan from a firm? For example, the site management had had an outside firm develop the management plan and Ephesus had become a UNESCO World Heritage Site. Otherwise, would the site management rely on their own experience this time? Was there another way?

The educators could use the case study to introduce graduate students to “the value conception” in “marketing management” courses and to “the social exchange school of thought” in “marketing theory” courses. The learning objectives develop over the tension between owning and outsourcing main responsibilities of a scientific field as well as the tension between claims and objective evaluations. “The value conception” in “the social exchange school of thought” could improve planning in favour of humanity in a way that the United Nations could recognise (e.g., “value-based planning”). Corresponding discussions motivate a main question about the future: What is marketing for?