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This study aims to provide insights into US and Australian analysts' views regarding the relative importance of disclosing the direct method (DM) or indirect method (IM) statement of cash flows and forecasting firm performance.

Evidence is collected from responses to 104 surveys and 52 interviews completed by US and Australian analysts from 2017 to 2022. The survey and interview questions are developed with reference to the literature.

US and Australian analysts believe that the DM format provides incremental benefits compared to the IM for (1) confirming the reliability of earnings; (2) improving earnings confidence; (3) more accurate ex ante forecasts of operating cash flow and earnings; and (4) identifying opportunistic accruals manipulation. Analysts view that DM disclosure can lower firm-level cost of equity, although US interviewees more uniformly expect lower costs of equity under DM disclosure when firms yield low earnings quality. DM disclosure is also more important during unstable economic periods, as proxied by COVID-19.

Limited research currently exists regarding disclosure of the DM or IM and its impact on analysts' forecasting accuracy, earnings quality, economic uncertainty and cost of equity. Previous research has relied on archival research to examine differences between the DM and IM methods and are limited by data availability. Our findings are particularly relevant to the US market with few US firms reporting the DM format.

The aim of this chapter is to reflect on the strengths of the different core concepts within the dual marketing (DM) arena; evaluate the strategic features of these core concepts in practice; assess how these concepts may provide insights into the development and management of DM; investigate how organisations manage their DM strategy and the extent to which stakeholders are involved in this process; explore how to manage and develop the DM strategy in different settings and contexts.

Data mining (DM) is used to improve the performance of manufacturing quality control activity, and reduces productivity loss. The purpose of this paper is to discover useful hidden patterns from fabric data to reduce the amount of defective goods and increase overall quality.

This research examines the improvement of manufacturing process via DM techniques. The paper explores the use of different preprocessing and DM techniques (rough sets theory, attribute relevance analysis, anomaly detection analysis, decision trees and rule induction) in carpet manufacturing as the real world application problem. SPSS Clementine Programme, Rosetta Toolkit, ASP (Active Server Pages) and VBScript programming language are used.

The most important variables of attributes that are effective in product quality are determined. A decision tree (DT) and decision rules are generated. Therefore, the faults in the process are detected. An on‐line programme is generated and the model's results are used to ensure the prevention of faulty products.

In time, this model will lose its validity. Therefore, it must be redeveloped periodically.

This study's productivity can be increased especially with the help of artificial intelligence technology. This research can also be applied to different industries.

The size and complexity of data make extraction difficult. Attribute relevance analysis is proposed for the selection of the attribute variables. The knowledge discovery in databases process is used. In addition, the system can be followed on‐line with this interactive ability.

The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

This study aims to propose a novel deep learning (DL)-based framework, iRelevancy, for identifying the disaster relevancy of a social media (SM) message.

It is worth mentioning that a fusion-based DL model is introduced to objectively identify the relevancy of a SM message to the disaster. The proposed system is evaluated with cyclone Fani data and compared with state-of-the-art DL models and the recent relevant studies. The performance of the experiments is assessed by the accuracy, precision, recall, f1-score, area under receiver operating curve and precision–recall curve score.

The iRelevancy leads to a better performance in accuracy, precision, recall, F-score, the area under receiver operating characteristic and area under precision-recall curve, compared to other state-of-the-art methods in the literature.

The predictive performance of the proposed model is illustrated with experimental results on cyclone Fani data, along with misclassifications. Further, to analyze the performance of the iRelevancy, the results on other cyclonic disasters, i.e. cyclone Titli, cyclone Amphan and cyclone Nisarga are presented. In addition, the framework is implemented on catastrophic events of different natures, i.e. COVID-19. The research study can assist disaster managers in effectively maneuvering disasters during distress.

Emerging market MNEs often seek to advance their domestic competitive advantage through a springboard FDI strategy, which typically takes the form of an acquisition into a developed market (DM) for knowledge resources. We argue that if this strategy is effective and beneficial, then an emerging market parent firm would seek for higher ownership and control in its later domestic acquisitions. Such benefits would be higher if there are richer knowledge resources in a DM subsidiary or in a DM local network. Such benefits would also increase over time because of the accumulation of new knowledge back home. Using a sample of 1,303 complete domestic acquisitions made by 713 Turkish firms over the period of 1987–2013, including 196 deals involving a springboard FDI strategy, we have found highly supportive empirical evidence. It is found that holding a DM subsidiary by a Turkish parent firm is associated with 33.047% higher ownership in a later domestic acquisition. Both research and practical implications are discussed.

The purpose of this paper is to examine the determinants of Greenfield emerging market (EM) outward foreign direct investment (OFDI) into the UK, a developed market (DM) host. Despite the increasing significance of EM OFDI, this particular theme of EM OFDI to a DM host has received relatively little attention from researchers. This paper seeks to address this shortfall.

Considering the distinctiveness of EM OFDI in its firm-specific characteristics, given circumstances and motivations, this paper applies adapted “Resource-based view (RBV)” framework and institutional theory to build a theoretical framework. A range of hypotheses regarding “strategic-asset seeking”, “market seeking” and “institution seeking” motivations of EM OFDI, which reflect both “pull factors” (advantages in hosts) and “push factors” (disadvantages at home), were then developed. Using panel data for the years 2003–2012, the research questions were analysed using a sample of the then most important EM source countries which had undertaken Greenfield FDI into the UK.

The analysis results supported the hypotheses that strategic-asset seeking and institution seeking motivations were important in determining EM OFDI to the UK, with the coefficients of relevant variables showing statistical significance and expected sign (i.e. positive). However, the hypothesis on market seeking motivation of EM OFDI cannot be supported as the coefficient of the relevant variable, whilst showing the expected sign, had a statistically insignificant coefficient. Amongst the three control variables, the source countries’ exports and imports as a percentage of GDP was statistically significant and had the correct sign whilst, the UK’s share of intra-EU trade, whilst statistically significant, had the opposite sign to that expected. The third control variable, the exchange rate was not statistically significant, though it had the correct sign.

This paper provides an adjusted theoretical framework for the analysis of EM OFDI to DM with a novel application of institutional theory and RBV. It also qualifies and extends existing works on EM OFDI by including a wider range of EM source countries and DM hosts with empirical analysis results as well as theoretical suggestions. In addition, the paper offers up a range of policy implications for DM hosts.

The purpose of this paper is to study current problems of implementing Diversity Management (DM) in businesses and presents a concept for measuring and estimating a value for diversity interventions.

An intellectual capital approach is used to identify a matrix of problems while implementing DM. To address the accounting problem for DM, advantages and disadvantages of the Diversity Scorecard are discussed and issues that require further conceptual development are identified.

Understanding DM as a part of intellectual capital helps solve accounting problems. The tests of the concept of Diversity Impact Navigator show that measuring DM at this stage requires a simple design, that using key indicators forces diversity interventions and that the process of valuation increases the understanding of DM by all stakeholders and thus its economic legitimation.

A newly developed concept helps solve the problem of measurement and valuation of DM. The paper presents the first test results.

The purpose of this paper is to introduce a digitalization model (DM) for building construction courses in architectural education as a response to the recent emerging technologies in the era of digital transformations. This DM is developed and applied through augmented reality (AR) technologies to boost perception, understandings and ability to solve building construction details.

Based on a thorough review of recent technologies like AR, virtual reality (VR), building information modelling (BIM) and their applications in architectural education, the methodology involves the generation of a model, its application and evaluation. The model is based on the integration of BIM and AR which is applied into a third year “Building Construction Project” course. Each student has designed a residential building and accordingly prepared the construction drawings by adapting the DM. An online survey –based on Technology Acceptance Model – is conducted to evaluate the DM by quantitative data analysis from SPSS and Excel.

The key findings of the study include the following items: determination of the proper digital tools, the definition of the steps and workflow based on the building project phases to develop construction drawings and define precise details effectively. By the help of this, the DM is generated and applied. According to the survey and results, the DM which involves BIM-based AR is considered as beneficial, highly motivating and providing better perception on construction details.

Implication of AR/VR technologies is frequently seen in design studios, whereas building construction courses state its traditional approach. However, there is a huge potential in the digitalization of building construction education by increasing the perception of students together with the increased level of communication. The study aims to close the gap of digitalization by proposing a DM, which brings a systematic approach considering each phase of building construction project as conceptual, schematic, design development and construction documents by using BIM integrated AR. Moreover, the novel model specifically brings a new approach by generation of QR codes for construction details to embed videos or simulations into the two-dimensional drawing sheets. Furthermore, the DM proposes a new approach to satisfy emerging needs and requirements of the Architecture Engineering Construction industry.

The purpose of this paper is to present a review of diversity management research published in hospitality and tourism-specific and business discipline-based journals. The study objectives include attempting to assess the progress of diversity management research in hospitality and tourism, identifying gaps between the general business diversity management literature and the hospitality and tourism literature and providing hospitality and tourism scholars with suggestions to advance knowledge in diversity management.

The study is a critical review of the existing diversity management literature in the general business and hospitality and tourism disciplines in an attempt to identify gaps and make suggestions for expanding this knowledge in the hospitality and tourism fields.

There are significant gaps between the diversity management scholarship conducted in hospitality and tourism disciplines and the general business field. Diversity management research in general business is far more in-depth and uses sociological and social psychological theoretical frameworks.

There are lessons to be learned from the general business literature that uses strong theoretical foundations deeply grounded in sociological, psychological, social-psychological and management theories. The general management literature also explores the conditions under which diversity management adds value or creates challenges for organizations.

The hospitality and tourism industry has employed large numbers of ethnic minorities, women and members of the lesbian, gay, bisexual and transgender community for decades. As such, it is critical that scholars explore the implications of such a diverse workforce not only on organizational outcomes, but also on individual and group performance. The general business diversity management research suggests that workgroup composition can influence individual and group performance, as well as the quality of co-worker relationships. Given the team-oriented, interdependent nature of work in the hospitality and tourism industry, it is imperative that researchers conduct studies that help practitioners understand the most effective perspectives and approaches to diversity management.

The critical literature review demonstrated that there is extremely scarce research on diversity management focusing on employees with disabilities. It is imperative to shed more light on best diversity management practices, workplace etiquette of this under-represented group of employees and their interaction with their co-workers.

This study’s results provide insight into areas of exploration that can significantly enhance the scholarship on diversity management in the hospitality and tourism literature.