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This paper offers a way of revivifying classical accounting research in the form of a pragmatist neoclassical programme with a sound epistemological underpinning.

The paper draws on a pragmatist perspective on financial accounting and accounting research springing from John Dewey's theory of inquiry.

Although a pragmatist underpinning does not entail specific methodological prescriptions, it can provide fruitful insights in research design. The paper discusses the structure and content of a research programme drawing on a pragmatist underpinning and sets out proposals for a practical research agenda. Although the agenda is shaped around the topic of identifiable intangibles, much of the paper has substantially wider relevance.

The approach justifies a revival in scholarly research employing classical methods and directed at improving accounting methods and standards.

The approach would promote closer engagement between scholarly accounting and practitioners such as standard-setters, making some contribution to closing the widely acknowledged gap between research and practice.

The paper offers a neoclassical programme of research drawing considerably more extensively on pragmatist philosophy than did theorisation in the classical period.

This research has the following specific objectives: provide an overview of the literature addressing operational excellence (OE) and OE in emerging countries; propose an integrative framework of OE attributes; and propose future research directions for the OE literature.

To remain competitive in industry, many organizations are implementing OE initiatives. However, achieving OE in emerging markets has been a pressing challenge due to the scarce knowledge on how it works. Through a systematic review of the literature, this study aims to contribute to a deeper understanding of the concept of OE in emerging countries through the triple bottom line.

This study has found nine attributes of OE based on the three pillars of sustainability or triple bottom line (economic, environmental and social). Four of them were the most cited and served to build the proposed framework. The analysis concludes that most of the studies related to OE in emerging countries have been carried out in Asia. Finally, based on the results obtained from the literature review, six points of future research are proposed based on three research directions: OE in emerging countries, active participation by employees and culture generation and finally, research methods.

The gap that is filled in this study is that some authors have studied the application of OE in emerging countries, specifically on the Asian continent. In those cases, the literature is either oriented to describing OE from different perspectives or to its application in different companies, some of which are emerging countries. However, to the best of the authors’ knowledge, there is no study that describes the specific and complete aspects that make up a model of OE and which can show how this model can be applied in emerging countries.

This research investigates the adoption of the industrial Internet of things (IIoT) in SMEs to achieve and increase organizational performance. With the latest technology, small and medium-sized enterprises (SMEs) can create a competitive edge in the market and better serve customers.

Twelve hypotheses are proposed for this study. This study constructed a questionnaire based on technological, organizational, environmental and human perspectives. A survey is conducted on the SMEs of India using the questionnaire.

Eight hypotheses were accepted, and four hypotheses were not supported. The hypotheses rejected are infrastructure, organizational readiness, internal excellence and prior experience. The findings suggested that adopting IIoT in SMEs will increase organizational performance.

This study will be helpful for the manager, top management and policymakers. This study identified the areas SMEs need to work on to adopt the technologies.

In the literature, no article considered IIoT adoption in SME firms as a human factor. Therefore, this study is unique, including human, technological, organizational and environmental factors.

One of the most important components of healthcare is the timely delivery of pharmaceutical products, such as life-saving medicines. However, disruptions like COVID-19 bring new challenges and risks to the pharmaceutical supply chain (PSC) and healthcare organizations that impact their operational performance. This study focuses on mitigating risks in India's generic medicine supply chain (GMSC) as a result of various disruptions, which can assist policymakers develop appropriate plans and strategies to build resilience in the Jan Aushadhi Scheme (JAS) of micro, small and medium enterprises (MSMEs) in order to improve their overall performance.

Risk-causing vulnerabilities and resilience capabilities are identified from the literature review and expert's opinions. Following that, the vulnerabilities are classified into cause-and-effect vulnerabilities, and supply chain resilient capabilities (SCRCs) are measured using a hybrid fuzzy DEMATEL and best worst method (FDEMATEL-BMW) framework.

The outcome of the study reveals that transportation breakdown, loss of human resources and loss of suppliers are the potential risk-causing vulnerabilities that lead to vulnerabilities like shortages of medicines, loss of in-hand stock qualities and loss of sales/revenue. In addition, the analysis suggests that the sustainability of an organization with maximum weightage is the critical factor for building resilience in GMSC followed by flexibility, agility and visibility.

The integration of resilience into Jan Aushadhi GMSC can help in managing disruptions efficiently and effectively to mitigate risk and optimize MSMEs overall performance.

To the best of the authors’ knowledge, this work will be the first of its kind to model resilience in GMSC of MSMEs using a hybrid framework.

This paper aims to uncover an understanding of how the quality assurance measures used by the property management teams of Grade-B high-rise office blocks influence the satisfaction and retention of tenants and walk-in users.

This study used a case study design backed up by qualitative and quantitative research approaches on a sample size of 90 respondents, including tenants, landlords, property managers and walk-in building users. The data were collected predominantly through interview guides and transcribed, coded and illustrated by the aid of ATLAS.ti software. Data reporting was through tables, graphs and themed direct quotations and eventual discussion. The in-depth/structured interview sessions took between 40 min and 1 h, and the walk-along interviews ranged between 30 and 40 min. Content analysis through thematic coding, categorisation and analysis were used in handling qualitative data. Direct quotes from participant responses from interview transcripts were inserted in line with the themes. And participants allocated pseudo-names to guard their confidentiality.

The key themes that linked quality assurance measures of access systems and tenant retention included distribution of access systems, the retention trends, quality assurance measures followed and the tenant experiences regarding how complaints are handled.

It is important to understand how tenants and other users of high-rise buildings experience their performance and inclusiveness. In a place like Kampala city, such a phenomenon can be proven through tenants sustaining their tenures/use of the facilities. Yet, to the best of the authors’ knowledge, presently no empirical studies have explored such a connection.

This paper proposes a maturity model to indicate the operational excellence (OE) implementation status of businesses in emerging countries, considering its importance in Industry 4.0.

The study involves four steps. First, undertake a study of the literature to identify the variables to consider in the maturity model; second, identify how to organize the variables found in the first step; third, structure a questionnaire to define the maturity model; and lastly, validate the variables found in the literature and the maturity levels.

A total of 23 variables were validated through interviews with general managers, operation managers and experts within organizations. Interviews were carried out in 49 companies from different sectors. Five maturity levels were defined in this study: basic level, beginner level, training level, innovative level and champion level.

Many businesses are implementing OE as a practice to remain competitive in their industries, targeting economic, environmental and social sustainability. However, OE implementation in companies from developing or emerging countries is far below the average level of that in developed companies due to cultural, political or economic constraints. To the best of the authors’ knowledge, there is no model that indicates the status of OE implementation in companies from emerging countries or the different levels to implement OE. This study fills the mentioned gap.

This paper aims to improve the life of the printed circuit boards (PCB) used in computers based on modal analysis by increasing the natural frequency of the PCB assembly.

In this work, through experiments and numerical simulations, an attempt has been made to increase the fundamental natural frequency of the PCB assembly as high as practically achievable so as to minimize the impacts of dynamic loads acting on it. An optimization tool in the finite element software (ANSYS) was used to search the specified design space for the optimal support location of the six fastening screws.

It is observed that by changing the support locations based on the optimization results the fundamental natural frequency can be raised up to 51.1% and the same is validated experimentally.

Manufacturers of PCBs used in computers fix the support locations based on symmetric feature of the board not on the dynamic behavior of the assembly. This work might lead manufacturers to redesign the location of other surface mount components.

This work provides guidelines for PCB manufacturers to finalize their support locating points which will improve the dynamic characteristics of the PCB assembly during its functioning.

This study provides a novel method to improve the life of PCB based on support locations optimization which includes majority of the surface mount components that contributes to the total mass the PCB assembly.

This study aims to empirically investigate the effect of International Financial Reporting Standards (IFRS) convergence on corporate risk disclosure, with a particular emphasis on the quantity and coverage of risk information. The research also conducts economic benefit and cost analysis to investigate the economic implications that may arise from the transition to IFRS reporting.

A content analysis approach is used to measure two broader dimensions of risk disclosure, namely, risk disclosure quantity and risk topic coverage. Furthermore, using firm-fixed effect regression on a sample of 143 Indian-listed companies, this study investigates the variations in these risk disclosure dimensions before (2012–2016) and subsequent to (2017–2021) the convergence with IFRS.

The empirical results of this research demonstrate that IFRS convergence has led to a significant improvement in firms’ risk disclosure across several dimensions. Particularly, during the post-IFRS period, firms’ usage of risk-related words and sentences has considerably surged in MD&A, Notes and whole annual reports. In addition, upon IFRS convergence, firms’ risk descriptions have become more extensive and evenly distributed across risk topic categories. Moreover, the in-depth benefit and cost analysis revealed that firms reporting under IFRS benefit from decreased cost of equity capital, but they also incur a higher cost of audit fees.

This study contributes to the literature in two ways. First, this is the only study, to the best of the authors’ knowledge, to conduct a broader examination of the impact of mandatory IFRS convergence on corporate risk disclosure, with a major focus on quantity and coverage of risk information. Second, by conducting economic benefit and cost analysis, this study provides novel insights into the critical role of IFRS risk disclosures toward multiple economic outcomes.

When a large number of project proposals are evaluated to allocate available funds, grouping them based on their similarities is beneficial. Current approaches to group proposals are primarily based on manual matching of similar topics, discipline areas and keywords declared by project applicants. When the number of proposals increases, this task becomes complex and requires excessive time. This paper aims to demonstrate how to effectively use the rich information in the titles and abstracts of Turkish project proposals to group them automatically.

This study proposes a model that effectively groups Turkish project proposals by combining word embedding, clustering and classification techniques. The proposed model uses FastText, BERT and term frequency/inverse document frequency (TF/IDF) word-embedding techniques to extract terms from the titles and abstracts of project proposals in Turkish. The extracted terms were grouped using both the clustering and classification techniques. Natural groups contained within the corpus were discovered using k-means, k-means++, k-medoids and agglomerative clustering algorithms. Additionally, this study employs classification approaches to predict the target class for each document in the corpus. To classify project proposals, various classifiers, including k-nearest neighbors (KNN), support vector machines (SVM), artificial neural networks (ANN), classification and regression trees (CART) and random forest (RF), are used. Empirical experiments were conducted to validate the effectiveness of the proposed method by using real data from the Istanbul Development Agency.

The results show that the generated word embeddings can effectively represent proposal texts as vectors, and can be used as inputs for clustering or classification algorithms. Using clustering algorithms, the document corpus is divided into five groups. In addition, the results demonstrate that the proposals can easily be categorized into predefined categories using classification algorithms. SVM-Linear achieved the highest prediction accuracy (89.2%) with the FastText word embedding method. A comparison of manual grouping with automatic classification and clustering results revealed that both classification and clustering techniques have a high success rate.

The proposed model automatically benefits from the rich information in project proposals and significantly reduces numerous time-consuming tasks that managers must perform manually. Thus, it eliminates the drawbacks of the current manual methods and yields significantly more accurate results. In the future, additional experiments should be conducted to validate the proposed method using data from other funding organizations.

This study presents the application of word embedding methods to effectively use the rich information in the titles and abstracts of Turkish project proposals. Existing research studies focus on the automatic grouping of proposals; traditional frequency-based word embedding methods are used for feature extraction methods to represent project proposals. Unlike previous research, this study employs two outperforming neural network-based textual feature extraction techniques to obtain terms representing the proposals: BERT as a contextual word embedding method and FastText as a static word embedding method. Moreover, to the best of our knowledge, there has been no research conducted on the grouping of project proposals in Turkish.

The purpose of this paper is to carry out a detailed analysis of two port converter fed by Solar and wind sources during different operational modes by small signal modelling. The converter is fully characterized and simulated using Matlab/Simulink. The voltage and current waveforms along with their corresponding expressions describing the converter operation are presented in detail. Then the DC-averaged equivalent topology is derived using circuit averaging technique. A complete derivation of the power stage transfer functions relevant to the capacitor voltage loop, such as capacitor voltage to solar voltage and inductor current to wind input voltage is obtained.

Stability analysis is used to analyze the small deviations around the steady-state operating point which helps in modeling the closed loop converter parameters. This paper presents the analysis, modeling and control of two port Cuk-buck converter topology.

Based on the results, a control strategy is designed to manage the energy flow within the system. A lab-level prototype for Cuk-buck converter with PWM controller is implemented and tested under various input conditions to study the performance of the converter during seasonal changes. The simulation and experimental results showed that effective operation and control strategy of the hybrid power supply system managed to be achieved alongside its feasible outputs.

This analysis can be extended to all power electronic converters and will be useful for the design of controllers.

An appropriate control design plays a key role in enhancing the overall performance of the system. Hence, this paper is intended to present in detail the small signal modeling of the Cuk-buck converter along with the control design for all the switching modes.

Though this type of converter topology has been discussed widely in literature, very scarce literature is available related to modeling and control design of the converter. A state-space averaging model of the converter followed by a type-II compensator design is described, and prototype design and experimental results are also presented.