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This study examines the association between the use of strategic management accounting (SMA) practices and competitive advantage and the moderating role of four aspects of organisational culture – teamwork orientation, outcome orientation, innovation orientation and attention to detail orientation – on this association. Online survey data were collected from 408 accountants in Australian business organisations, and structural equation modelling (SEM) was used to analyse the data. The results indicate a positive association between the use of SMA practices and competitive advantage with such an association positively moderated by one cultural dimension, teamwork orientation. Specifically, the findings indicate that the positive effect of SMA practices on competitive advantage is dependent upon the fit between the use of SMA practices and teamwork orientation with more (less) teamwork-oriented organisations exhibiting a stronger (weaker) association between the use of SMA practices and competitive advantage.

In recent years, researchers and practitioners have paid a great deal of attention to the circular economy (CE) due to its potential social and environmental benefits. However, limited attention has been devoted in the literature to studying the barriers to CE implementation in the apparel retail industry in emerging and developing nations besides China. Consequently, the purpose of this paper is to analyse the barriers to implementing CE in the Indian garment retail market.

This exploratory study uses a comprehensive literature analysis to identify the micro-level impediments to CE adoption in India's garment retail industry. The study aims to identify these barriers using a Delphi process, consisting of three stages. The first stage involves literature reviews and expert opinions, while the second and third stages involve survey methods with 14 industry professionals and academics. The use of the two primary data sources allows for triangulation of the data, which improves the validity of the findings and enables broader conclusions to be drawn from the results.

This study indicates that the top three challenges to implementing CE principles in the Indian apparel retail industry are “standards and regulation barriers” (84%), “strategic barriers” (82%) and “supply chain management and technology barriers” (79%). Strategies for overcoming these obstacles include gaining top management support, coordinating supply chain components, training and employee motivation.

This study considers only Indian apparel retail industry, and the practical implications could potentially limit the study to emerging Asian economies.

To the best of the authors’ knowledge, this is the first research of its type to explore CE obstacles at the organizational level in the Indian garment retail business. Thus, it contributes to a greater understanding of the topic and enables practitioners to develop effective policies and business strategies for CE and sustainability.

The purpose of this paper is to study the crisis management process for project-based organizations (PBOs) by developing a comprehensive model and propositions.

This paper is based on a conceptual study. A literature review is considered a primary source for studying contemporary research, including 171 publications in total, which embody qualitative, quantitative, conceptual and theoretical studies. For data analysis, content analysis is used, which is comprised of descriptive and thematic analysis.

This study identifies five imperative elements of crisis management for PBOs which include (1) sense-making (information gathering and crisis interpretation), (2) decision-making (accurate and timely decision), (3) response (reactive response), (4) outcome (success/failure) and (5) learning. Based on these findings, this study proposes an integrative model of the interplay between sense-making, decision-making, response, outcome and learning. Furthermore, the findings lead to propositions for each of the elements. The paper contributes to the literature on dynamic capability theory.

This paper explores the crisis management process for PBOs. The proposed model deepens the understanding of the practices and processes of project-based crisis management.

This study aims to reveal the constituents of seafaring service quality (physical and social environment) and their effects on seafarer employee satisfaction (job satisfaction and turnover intention) and analyse any differences among seafarer ranks. Literature on service quality has overlooked the transportation sector and seafaring in particular.

Seafaring service quality is measured by the workplace environment constituted of physical and social environments. Two types of employee (job) satisfaction were explored: overall job satisfaction and turnover intention. This study is based on a unique, large survey based on the Existence-Relatedness-Growth (ERG) needs theory. An exploratory factor analysis revealed four physical environment factors (Ship conditions, Communication facilities, Nautical health and Living conditions) and four social environment factors (Social fit, Team cohesion, Ship company support and Intercultural environment). Multi-group regression analysis assessed the effects of seafaring service quality on employee satisfaction.

The social environment has stronger effects than the physical environment on job satisfaction but not on employee retention. Team cohesion has strong effects on employee retention, while social fit has stronger effects on overall job performance. Seafarer ranks showed significant variations. The physical environment matters for 2nd engineers' and cadets’ job satisfaction but not for ratings, masters and chief officers. Team cohesion is significant to master, chief officer, engineer and cadet ranks but not for junior officers and ratings. Social fit has stronger effects on overall job performance than employee retention, particularly for ratings, cadets, master, chief officer and chief engineer ranks. Ship company support has the stronger effect on overall job satisfaction among all workplace factors; this is also observed across all ranks.

Motivation theories like the ERG theory can help understand service quality and employee satisfaction in the maritime sector; future studies should examine more behaviour variables/constructs from these theories.

Maritime companies can offer better services to seafarers, who are considered as key workers, by customising their interventions to specific seafarer ranks and developing a supportive culture that improves seafarer well-being.

This study examined the overlooked topic of maritime service quality based on a large-scale survey grounded on ERG theory and reveals how the physical and social environment has different effects on seafarer job satisfaction and retention.

The study aims to facilitate the medical tourists visiting emerging countries for various kinds of ailments by ranking the possible destinations to avail medical treatments.

A Fuzzy Analytical Hierarchical Process (FAHP) with a mixed-method approach is applied to analyze data collected from patients and substantiate it with medical tour operators in India to gain managerial insights on the choice-making patterns of the patients.

India is a preferred emerging market location due to the low cost and high medical staff quality. India offers value for money, whereas Singapore and Thailand are preferred destinations for quality and technology.

The study will facilitate the emerging markets' governments, hospitals and medical tourists to understand the importance of various determinants responsible for availing medical treatment outside their country.

The study recommends that cost and quality care are the patients' prime focus; government policies must provide clear guidelines on what the hospitals and country environment can offer and accordingly align the marketing strategies.

This study is the first attempt to rank various factors affecting medical tourism using the FAHP approach.

The study aims to provide insights in the sensemaking process and the use of business analytics (BA) for project selection and prioritisation in start-up settings. A major focus is on the various ways start-ups can understand their data through the analytical process of sensemaking.

This is a comparative case study of two start-ups that use BA in their projects. The authors follow an interpretive approach and draw from the constructivist grounded theory method (GTM) for the purpose of data analysis, whereby the theory of sensemaking functions as the sensitising device that supports the interpretation of the data.

The key findings lie within the scope of project selection and prioritisation, where the sensemaking process is implicitly influenced by each start-up's strategy and business model. BA helps start-ups notice changes within their internal and external environment and focus their attention on the more critical questions along the lines of their processes, operations and business model. However, BA alone cannot support decision-making around less structured problems such as project selection and prioritisation, where intuitive judgement and personal opinion are still heavily used.

This study extends the research on BA applied in organisations as tools for business development. Specifically, the authors draw on the literature of BA tools in support of project management from multiple perspectives. The perspectives include but are not limited to project assessment and prioritisation. The authors view the decision-making process and the path from insight to value, as a sensemaking process, where data become part of the sensemaking roadmap and BA helps start-ups navigate the decision-making process.

GraphQL is a new Open API specification that allows clients to send queries and obtain data flexibly according to their needs. However, a high-complexity GraphQL query may lead to an excessive data volume of the query result, which causes problems such as resource overload of the API server. Therefore, this paper aims to address this issue by predicting the response data volume of a GraphQL query statement.

This paper proposes a GraphQL response data volume prediction approach based on Code2Vec and AutoML. First, a GraphQL query statement is transformed into a path collection of an abstract syntax tree based on the idea of Code2Vec, and then the query is aggregated into a vector with the fixed length. Finally, the response result data volume is predicted by a fully connected neural network. To further improve the prediction accuracy, the prediction results of embedded features are combined with the field features and summary features of the query statement to predict the final response data volume by the AutoML model.

Experiments on two public GraphQL API data sets, GitHub and Yelp, show that the accuracy of the proposed approach is 15.85% and 50.31% higher than existing GraphQL response volume prediction approaches based on machine learning techniques, respectively.

This paper proposes an approach that combines Code2Vec and AutoML for GraphQL query response data volume prediction with higher accuracy.

This study aims to address the current gap in knowledge of indirect procurement performance management. It attempts to argue the need for a specific and tailored performance management approach for the indirect procurement function that incorporates a balanced approach, beyond financial measures.

The case study approach evaluated key performance indicators from a balanced scorecard (BSC) perspective in the development of a performance measurement system (PMS) for a Middle Eastern university’s indirect procurement division. It initially reviewed the literature to assess potential indicators for this context. It used vision and mission statement analysis alongside expert interviews to augment the literature. The candidate indicators were then evaluated and ranked by an expert panel through applying a four-round Delphi technique.

Twenty-nine procurement-specific indicators are suggested in a BSC framework. The five highest-ranked indicators were not in the financial perspective unlike other BSC studies in the broader field of supply chain management (SCM).

The study suggests a framework and indicators for a procurement PMS for practitioners to consider. It also highlights there is no one-size-fits-all and that organisations need to tailor PM to the organisation and divisional strategy and operational needs. This study aids the development of guidelines for executives and procurement management that wish to develop indicators and a PMS.

This study contributes to knowledge by partly addressing the under-researched field of indirect procurement PM. The literature suggested that various roles in SCM require specific PM indicators. This study puts forward a BSC framework with 29 indicators specifically for indirect procurement. Fourteen of these indicators were derived from non-literature sources. This study enhances knowledge and contributes to the limited debate and evidence on indirect procurement PM and the broader PM literature.

This study aims to analyze how the interplay between hard and soft elements of total quality management (TQM) produces the conditions for sustaining success in the quest for quality.

A qualitative analysis (Gioia method) was carried out on an original dataset collected through both direct and indirect methods (i.e. archival sources, interviews and observations) to generate a new interpretive framework.

The interpretative framework identifies four categories of elements: trigger elements create the starting conditions for a quality virtuous cycle; benchmarking tools set the standards of performance; improvement tools enable exploration of the space of possible alternative practices and finally, catalytic forces allow the institutionalization of effective techniques discovered in this search process into new standards.

The findings the authors present in this paper are derived by a single case study, limiting the generalizability of our results in other settings.

This study has three implications: first, the design of trigger elements is critical for the success of any TQM initiative; second, the interplay of improvement and benchmarking tools at several levels should be coherent and third, to exploit the potential of TQM, efforts should be devoted to the dissemination of new effective practices by means of catalyzing elements.

The model provides a more specific understanding of the nature and purpose of the hard and soft elements of TQM and the dynamic interaction between the two classes of elements over time.

Effective total quality management (TQM) practices rely on the accurate classification of critical success factors (CSFs). The impact matrix cross-reference multiplication technique for classification (MICMAC) or/and fuzzy MICMAC (FMICMAC) can be used to identify key factors in the complex set. However, TQM includes both “hard” and “soft” factors, limiting application of the traditional MICMAC/FMICMAC method.

Previous literature on TQM was reviewed, CSFs were identified, and factors were sorted into soft and hard categories. The combined fuzzy integration and dual-aspect MICMAC (fuzzy dual-aspect MICMAC approach) was then applied to identify, cluster and prioritize the CSFs of TQM.

A total of 20 factors (10 soft and 10 hard) were identified and isolated to assess the manufacturing- and service-related TQM practices of the Pearl River Delta Region of China. Seven driver factors and one linkage factor emerged as the key CSFs that managers should prioritize.

A major limitation of this study is the dependency of the results on the definitions of linguistic labels. If the linguistic definitions of TQM CSFs do not closely correspond to the expert opinion data, then the analysis results may be inaccurate. Additionally, although expert opinions are utilized in the proposed method for comprehensive assessments, these opinions may influence the final results due to their inherent subjectivity.

A novel fuzzy dual-aspect MICMAC approach was developed to identify and classify CSFs for optimal TQM practices. This approach allows clustering of CSFs so that decision-makers can prioritize factors according to their dependence and driving powers. Practitioners should concentrate on the CSFs with higher driving powers for successful TQM.