Search results

Health-care organisations face many challenges in delivering safe, high-quality services while experiencing significant pressure to increase productivity and reduce costs. In this context, hospitals have implemented lean six sigma (LSS) programmes to improve their performance. This study aims to explore the application of LSS in three different non-profit Ecuadorian hospitals to comprehend the effectiveness of the methodology under this context.

A multiple-case analysis was performed in four phases: selecting the cases, defining a data collection protocol, performing a within-case analysis of each case and performing a cross-case analysis.

This research found that the LSS application positively impacts hospital performance indicators by reducing service time. The most frequently used tools include the supplier input process output customer diagram, value stream mapping, cause-and-effect diagram, five-why analysis, Gemba walk and paired two-sample test. Lastly, the results show that the most common challenges faced were lack of top management engagement, technical training and data availability.

The study is limited by the constraint of a single Latin American country from which the cases were analysed. Collaboration with external partners, like universities, and government policies promoting training in continuous improvement methodologies are crucial for success. Academic implications stress the importance of integrating soft skills in LSS implementation and engineering education.

This study shows a multiple-case analysis of LSS in a Latin American country highlighting the most commonly used tools, their impact on performance and the challenges of implementing LSS in health-care organisations in non-profit Ecuadorian hospitals.

The aim of this research is to explore how a programmatic multi-project context influences project-based firms (PBFs) in organizing their relations with other PBFs and suppliers in a project-based industry.

A multiple case study research is conducted. Data are collected from two case studies in the construction infrastructure sector. Eleven interviews with contractors and other suppliers are the primary source of data collection. The data are complemented by procurement documents and expert consultations.

The findings show that within a programmatic multi-project context, PBFs settle relations with (1) key partners for program management capacity, PBFs establish relations with (2) main contractors to divide projects and (innovation) tasks, and PBFs intensify relations with (3) suppliers to ensure continuity and expertise.

The study contributes to the body of project management literature by exploring PBF’s relations with other PBFs and suppliers in a multi-project context. Based on empirical data, the study provides a distinction in layers presenting distinct levels of PBF’s supplier relations. This layer structure provides an excellent starting point for future studies exploring the program perspective of PBFs in the integrated supply chain.

Given the increase in programmatic multi-project context for project-based domains, discussed in both literature and practice, this study explores the effect of programs on relations of PBFs with other PBFs and suppliers. The study distinguishes PBF’s relations with the different suppliers in three layers and discusses the characteristics of these relations.

This study aims to investigate the impact of changes in audit processes during the pandemic on auditors’ deviant behavior, considering auditors’ personal characteristics, including demographic variables, spirituality levels and personality traits.

A survey consisting of five parts was used to gather data from auditors employed at Big Four audit firms in the Middle East. The questionnaire collected data on auditors’ perceptions of changes in audit processes and deviant audit behavior during the pandemic, as well as information about their personal characteristics.

The findings revealed a significant positive association between changes in audit processes and a heightened perception of deviant audit conduct during the pandemic. Males and extravert auditors expressed less favorable attitudes toward such behavior.

The sample size was limited to 107 auditors due to the challenges of soliciting responses from auditors during the pandemic. The sole focus on the Big Four audit firms limited the generalizability of the results. Upcoming research should integrate qualitative methods alongside surveys and collect data from larger, more diverse samples to enhance the understanding of the pandemic’s impact on audit behavior.

The findings provide guidance and recommendations for audit firms to mitigate deviant behavior during crises while considering auditors’ personal factors. Recommended strategies include the organization of trainings to raise awareness of these risks and the integration of artificial intelligence to modernize audit processes and enhance audit firms’ readiness to confront future crises.

This study offers a novel empirical investigation into how pandemic-driven changes in audit procedures relate to auditors' deviant behavior, while exploring the influence of auditors' individual traits, an unexplored area in the literature. It addresses this gap specifically in the context of the understudied Middle East region.

This study aims to estimate the amount of money laundering (ML) with multiple proxy approaches and measure the effects of ML on various indicators of the economic and financial sectors. Theoretical justifications are recruited from the parasite theory of organised crime.

A quantitative research methodology was used on a balanced panel data set to test the study’s hypothesis through generalised method of moment (GMM). The study sample consisted of 77 countries, and the data was collected for 15 years (2005–2019).

A study has found that 1.23% of global gross domestic product is laundered yearly, and there is no noticeable decline in ML activities. Further study has also found that ML has devastating effects on countries, government revenue, foreign investment, economic development, political and peace conditions, bank liquidity, interest rate volatility and exchange rate volatility. The study has not witnessed the negative consequence of ML on countries’ inflation rates.

Estimates of the study guide policymakers about the volume of resources fleeing and helps them to decide the level of response needed. Further findings help them prioritise the response system according to the area most affected.

This study is an original contribution by the authors and has studied the effects of ML by computing the amount of ML by four different proxies.

Foreign subsidiaries of multinational enterprises (MNEs) operate in complex and competitive international environments, implement market and non-market strategies, manage resources and value-added activities and contribute to the overall performance of their parent firms. Thus, the research question on the determinants of MNE foreign subsidiaries’ performance is of interest to managers and academic researchers. The empirical literature has flourished over the recent decades; however, the domains are fragmented, and the findings are inclusive. The purpose of this study is to systematically review, analyse and synthesize the empirical articles in this area, identify research gaps and suggest a future research agenda.

This study uses the qualitative content analysis method in reviewing and analysing 150 articles published in 24 scholarly journals during the period 2000–2023.

The literature uses a variety of theoretical perspectives to examine the key determinants of subsidiary performance which can be grouped into six major domains, namely, home- and host country-level factors; distance between home and host countries; the characteristics of parent firms and of subsidiaries; and governance mechanisms (the establishment modes and ownership strategy, subsidiary autonomy and the use of home country expatriates for transferring knowledge from the headquarters and controlling foreign subsidiaries). A range of objective and subjective indicators are used to measure subsidiary performance. Yet, the research shows a lack of broader integration of theories and presents inconsistent theoretical predictions, inconclusive empirical findings and estimation bias, which hinder our understanding of how the determinants independently and jointly shape the performance of foreign subsidiaries.

This study provides a comprehensive, nuanced and systematic review that synthesizes and clarifies the determinants of subsidiary performance, offers deeper insights from both theoretical, methodological and empirical aspects and proposes some promising avenues for future research directions.

Text classification is a widely accepted and adopted technique in organizations to mine and analyze unstructured and semi-structured data. With advancement of technological computing, deep learning has become more popular among academicians and professionals to perform mining and analytical operations. In this work, the authors study the research carried out in field of text classification using deep learning techniques to identify gaps and opportunities for doing research.

The authors adopted bibliometric-based approach in conjunction with visualization techniques to uncover new insights and findings. The authors collected data of two decades from Scopus global database to perform this study. The authors discuss business applications of deep learning techniques for text classification.

The study provides overview of various publication sources in field of text classification and deep learning together. The study also presents list of prominent authors and their countries working in this field. The authors also presented list of most cited articles based on citations and country of research. Various visualization techniques such as word cloud, network diagram and thematic map were used to identify collaboration network.

The study performed in this paper helped to understand research gaps that is original contribution to body of literature. To best of the authors' knowledge, in-depth study in the field of text classification and deep learning has not been performed in detail. The study provides high value to scholars and professionals by providing them opportunities of research in this area.

This paper aims to conduct a bibliometric analysis of studies focusing on green supply chain management (GSCM) within the context of the digital economy.

We utilize the Web of Science database to search and filter relevant documents spanning the years 2003–2022. This extensive dataset enables us to analyze the growth and cutting-edge developments in research pertaining to GSCM in the digital economy.

The paper finds a significant increase in research interest and output, particularly noticeable from 2016 onwards, indicating the growing relevance of integrating GSCM with digital technologies. It is found that the prominent contribution of countries like China, England and the USA, underscoring a strong geographical diversity in research outputs. China leads in the number of publications, which reflects its significant role in shaping the discourse around GSCM in the digital economy. However, when it comes to citations, the USA leads, suggesting a higher impact or quality of research emanating from this region. Collaborative dynamics outlined in the study demonstrate extensive international cooperation, primarily among leading research countries, which is facilitated by shared digital platforms enhancing the research’s reach and impact. The study also highlights a range of emerging themes such as the adoption of blockchain technology, Internet of Things (IoT) and the circular economy within GSCM, indicating dynamic areas for future research.

The findings of this study hold significant practical implications for researchers, practitioners and policymakers. They shed light on the current state of research in GSCM within the digital economy, highlighting areas where further investigation is needed and pointing to the emerging trends in this field. Understanding the distribution of research and influential authors can guide future collaborative efforts and inform decision-making processes in the pursuit of sustainable supply chain practices in the digital era.

This paper contributes to the existing body of knowledge by providing a comprehensive bibliometric analysis of the evolving landscape of GSCM in the digital economy. It offers valuable insights into the growth patterns, key contributors and geographical distribution of research in this domain. This information is crucial for researchers and stakeholders seeking to stay at the forefront of sustainable supply chain practices in an increasingly digital world.

Through the subject of business network dynamics, this study aims to examine how business network relationships impact company entry market and development within fast growing economies as China. The paper looks at business network relationships in a fast-growing economy and provides an understanding of the relational perspectives in internationalisation of three luxury fashion companies and their entry models affected by the China context-related variables.

The methodology is following a qualitative approach, based on multiple case-studies research, proposing three cases of companies entering the Chinese market in the luxury and fashion industry.

The research analyses the local business network paths and how they affect the entry strategy through the socio-cultural and political players. The paper adds knowledge to studies in market entry and business networks, in the fast-growing economies area, with its new norms and values.

This study tries to analyse how business networks and related relationships “with Chinese characteristics” affect the market entry strategy in the internationalisation path from the perspective of the luxury fashion industry sector. In so doing it tries to provide an original further development of business network models within the new Chinese context.

This study investigates barriers to consumers’ organic food purchasing. It identifies the factors and the extent to which they influence their purchase behaviours and future purchase intentions (i.e. continuance purchase intentions).

It combines qualitative and quantitative methods across two phases. Longitudinal research was carried out in two phases. It involved a thematic analysis and a covariance-based structural equation modelling approach. During Phase-1 and Phase-2, responses were collected from 376 and 351 respondents, respectively.

Phase 1 found the value barrier was significantly affecting the consumers’ purchase intention, while Phase 2 identified the impacts from both image and value barriers on purchase intentions. Notably, purchase intention affected continuance intention in both phases, while ethnocentrism showed no influence.

Using the innovation resistance theory, this study sheds light on the factors that prevent purchase intention. It offers valuable insights for policymakers and for the marketers of organic foods. This contribution implies that value and usage barriers were affecting the consumers’ purchase intentions in the short as well as in the long term. In sum, it suggests that consumers were not purchasing organic food as they felt it was either overpriced, not available in the market or because they were sceptical about its organic labelling.

The COVID-19 pandemic showed that preestablished contingency plans and resilience practices were insufficient to cope with long-term and global disruptions. Companies thus struggled to develop capabilities that ensure their survivability during similar crises. Building on the adaptation-based view (ABV) of supply chain resilience, this study aims to offer an in-depth perspective on survivability in supply chains (SCs).

The paper empirically tests related relationships between adaptation capabilities and practices that ensure operational continuity. Responses from 252 organisations were collected and analysed using partial least squares structural equation modelling.

The results empirically support the ABV’s theoretical propositions and assess the possibilities of intertwining, digitalisation, a circular economy and maturity for the survivability of SCs.

The derived insights are attractive for managers and researchers to foster supply chain survivability and contribute to the increasing efforts of middle-range theorising in logistics and supply chain management research.

To the best of the authors’ knowledge, this study is one of the first studies to define factors enhancing the survivability of SCs through the lens of the ABV.