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Continuous improvement in an integrated approach is a philosophy developed over decades based on a set of management practices. It comprises enhancement methodologies that escalate success as well as diminishes letdowns. The state-of-the-art literature finds a variety of practices for the execution of continuous improvement (CI) system. However, it is rare to find an empirical study with an inclusive system that considers various practices in one frame for improving competitiveness. With this outlook, therefore, this study aims originally to identify drivers, motivations and barriers for the application of integrated CI system, and then conduct an empirical investigation within the context of Ethiopian manufacturing industries.

Justification of the problem, extensive review of literature, identification of practices, developing research framework, investigational analysis of the empirical study using reliability and descriptive statistical analysis and identifying leading drivers (unique practices and common factors), motivations and barriers are the research approaches used in this study. Furthermore, the primary data were collected through a self-administered questionnaire and were analyzed using a statistical package for social science (SPSS) 23 and the findings were triangulated to relate to the existing state-of-the-art literature.

The findings indicate 17 common factors associated with human, strategic, operational, technology, structure, resource and information factors; 21 unique practices of just-in-time (JIT), lean-six sigma (LSS), supply chain management (SCM), total productive maintenance (TPM), and total quality management (TQM) methodologies; 20 barriers connected with internal and external issues and 17 motivations linked to operational, innovation and business results are identified. In general, the empirical analysis discovers the practices are noteworthy and commonly supported by a least of 52% of the respondents. As a result, the first five prominent common factors, barriers, unique practices and motivations are also supported by a minimum of 72%, 73.9%, 65.8% and 75% of the respondents, respectively.

Even though this is the first-ever study in the Ethiopian manufacturing sector with the focus on integrated CI practices of JIT, TQM, TPM, SCM and LSS initiatives, some limitations have existed and the major limitations of the study are, targeted merely small number manufacturing companies despite the fact that there are hundreds of companies implementing CI system in Ethiopia, and the data collected were only based on the perception of the respondents, and other information’s like annual reports was not employed to support the findings.

The findings of this study underlined that the implementation of drivers in relation to common factors and unique practices supported by exterminating barriers in manufacturing industries of Ethiopia enables to enhance competitiveness through attaining operational, innovation and business results though it requires a practical case application to prove this perception-based analysis.

Though there are a number of studies published on integrated continuous improvement, currently it is found that there is no literature focused on the identification and empirical investigation of drivers (common factors and unique practices), motivations and barriers for application of integrated CI system with the focus of JIT, TQM, TPM, SCM and LSS initiatives. Therefore, this is the first-ever study, and the empirical analysis of the study discovered that identified practices are providing valuable insights for manufacturing industries which will be on board on this voyage including institutions, practitioners and other sectors.

The rise of artificial intelligence (AI) applications has driven enterprises to provide many intelligent services to consumers. For instance, customers can use chatbots to make relevant inquiries and seek solutions to their problems. Despite the development of customer service chatbots years ago, they require significant improvements for market recognition. Many customers have reported negative experiences with customer service chatbots, contributing to resistance toward their use. Therefore, this study adopts the innovation resistance theory (IRT) perspective to understand customers’ resistance to using chatbots. It aims to integrate customers’ negative emotions into a predictive behavior model and examine users’ functional and psychological barriers.

In this study, we collected data from 419 valid individuals and used structural equation modeling to analyze the relationships between resistance factors and negative emotions.

The results confirmed that barrier factors affect negative emotions and amplify chatbot resistance influence. We discovered that value and risk barriers directly influence consumer use. Moreover, both functional and psychological barriers positively impact negative emotions.

This study adopts the innovation resistance theory perspective to understand customer resistance to using chatbots, integrates customer negative emotions to construct a predictive behavior model and explores users’ functional and psychological barriers. It can help in developing online customer service chatbots for e-commerce.

Building information modelling (BIM) implementation in the design, construction and operations (DCO) industry is increasingly becoming essential. While BIM has been adopted on a larger scale in many developed economies, its acceptance is still in the embryonic phases for developing nations in the DCO industry. This study aims to identify the inhibitors to BIM implementation through the social network theoretical lens, intending to understand the associations among the barriers in the Indian context. Subsequently, recommend strategies to mitigate the barriers from the academic practitioner’s perspective.

A mixed methods research was adopted, commencing with comprehensive literature reviews to recognise various inhibitors to BIM implementation. These identified barriers were further examined through the questionnaire survey (n = 71). BIM implementation barrier network (BIBN) was created using University of California at Irvine Network (UCINET) is a powerful social network analysis software that functions on the principle of social network theory. The experts’ opinions were captured through the BIBN network through interviews. Network properties such as eigen vector centrality, betweenness centrality, degree centrality, in-degree and out-degree and clustering coefficient were computed, and the metrics were analysed further.

Twenty-six BIM implementation barriers were initially identified. A questionnaire survey was conducted. The chain reaction can be minimised by prioritising and regulating these barriers. The issues were categorised into fourfold clusters (standardisation, policy and process, cultural and human resources, change management and operational) issues were generated from the exploratory factor analysis (EFA). The obstacles and barriers resulting from the other main barriers associated with it can be minimised by reducing the challenges with high eigenvector centrality but low betweenness importance.

This study proves to accelerate sustainable BIM implementation growth in developing nations; this research study assists BIM stakeholders in developing coping mechanisms to monitor and remove BIM implementation barriers.

Analysing the associativity of the BIM implementation barriers through sociograms for developing nations is a novel concept with this research.

The present study aims to identify significant barriers to adopting prefabricated construction (PFC) in developing economies using a study in Sri Lanka and develop an integrated strategy framework to mitigate and overcome the obstacles.

The research process included a comprehensive literature review, a pilot study, a questionnaire survey for data collection, statistical analysis and a qualitative content analysis.

Ranking method revealed that all 23 barriers were significant. Top significant barriers include challenges in prefabricated component transportation, high capital investment costs and lack of awareness of the benefits of PFC among owners/developers. Factor analysis clustered six barrier categories (BCs) that fit the barrier factors, explaining 71.22% of the cumulative variance. Fuzzy synthetic evaluation revealed that all BCs significantly influence PFC adoption in Sri Lanka. Finally, the proposed mitigation strategies were mapped with barriers to complete the integrated framework.

The study outcomes are relevant to construction industry stakeholders of Sri Lanka, who are keen to enhance construction efficiencies. The implications can also benefit construction industry stakeholders and policymakers to formulate policies and regulations and identify mitigation solutions.

The study provides deeper insights into the challenges to adopting prefabrication in South Asian countries such as Sri Lanka. Furthermore, the integrated framework is a novel contribution that can be used to derive actions to mitigate barriers in developing economies.

The purpose of this study is to empirically examine the relationships between barrier-breakers and customers’ intention to fully adopt digital payment methods (DPMs).

Survey data were analyzed using statistical methods focusing on hypothesis testing with an ordinal regression model and moderation analysis using the PROCESS macro extension. Participants were divided into two groups of customers in Sweden: adopters-accepters, i.e. young bank customers and adopters-resisters, i.e. members of a formally organized group opposed to a cashless society.

The findings revealed that only the credibility barrier-breaker could increase the adopters-accepters’ intention to fully adopt DPMs. Credibility also seemed to be an important barrier-breaker for the adopters-resisters, as were perceived usefulness and social influence. Additional analyses showed that the impersonalization barrier reduces the impact of the barrier-breakers on DPM adoption.

Retail banks and merchants can use these results as a guide to what barrier-breakers might affect various customers’ intention to fully adopt DPMs, and to act accordingly. The impersonalization barrier also merits attention when creating an emotional connection to customers who use DPMs.

This study provides empirically based knowledge of the influence of barrier-breakers on the intention of customers, categorized as adopters-accepters and adopters-resisters, to fully adopt DPMs, and highlights the importance of maintaining a human touch in the post-COVID-19 digital era.

The objective of this research is to investigate the barriers impacting the integration of Industry 5.0 (I5.0) in supply chain sustainability. By understanding these challenges, this study aims to provide valuable insights that can guide organizations in successfully implementing the transformative potential of I5.0. The ultimate aim is to improve operational efficiency and advocate for sustainable practices within supply chains.

Research has used industry expert interviews, a comprehensive literature review and the decision-making trial and evaluation laboratory approach for analysis. Industry expert interviews serve to capture first-hand insights from professionals well versed in the field, providing practical perspectives on the barriers to I5.0 adoption.

This study identifies technological challenges, organizational barriers, regulatory impediments and economic constraints as pivotal factors inhibiting the widespread adoption of I5.0 in supply chain sustainability.

This research serves as a foundation for future investigations into overcoming barriers to I5.0 adoption, guiding scholars and practitioners in refining strategies for successful implementation.

The findings offer practical insights for organizations aiming to adopt I5.0, informing decision-makers on key challenges and facilitating the development of targeted strategies to overcome them.

The social implications lie in fostering sustainable business practices through the adoption of I5.0, contributing to environmental responsibility and societal well-being.

This research contributes original insights from practitioners, policymakers and researchers in navigating the complex landscape of I5.0 adoption, ensuring meaningful contributions to both academia and industry.

This study aims to address the critical challenge of implementing lean manufacturing (LM) in emerging economies, where sustainability complexities on the production floor hinder production efficiency and the transition towards a circular economy (CE). Addressing a gap in existing research, the paper introduces a path analysis model to systematically identify, prioritize and overcome LM implementation barriers, aiming to enhance performance through strategic removal.

The authors used a mixed-method approach, combining empirical survey data with literature reviews to pinpoint key LM barriers. Using the grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL) along with the Network Knowledge (NK) method, they mapped causal relationships and barrier intensities. This formed the basis for developing a path simulation algorithm, integrating heuristic considerations for practical decision-making.

This analysis reveals that the primary barriers to LM adoption is the negative perception and inadequate understanding of lean tools and CE principles. The study provides a strategic framework for managers, offering new insights into barrier prioritization and overcoming strategies to facilitate successful LM adoption.

This research provides a strategic pathway for overcoming LM implementation barriers, empowering managers in emerging economies to enhance sustainability and competitive advantage through LM and CE integration. It emphasizes the significance of structured barrier management in the manufacturing sector.

This research pioneers a systematic exploration of LM implementation barriers in the CE context, making a significant contribution to the literature. It identifies, evaluates barriers and proposes a practical model for overcoming them, enriching sustainable manufacturing practices in emerging markets.

Previous research has demonstrated that Digital Twins (DT) are extensively employed to improve sustainable construction methods. Nonetheless, their uptake in numerous nations is still constrained. This study seeks to identify and examine the digital twin’s implementation barriers in construction building projects to augment operational performance and sustainability.

An iterative two-stage approach was adopted to explore the phenomena under investigation. General DT Implementation Barriers were first identified from extant literature and subsequently explored using primary questionnaire survey data from Hong Kong building industry professionals.

Survey results illustrated that Lack of methodologies and tools, Difficulty in ensuring a high level of performance in real-time communication, Impossibility of directly measuring all data relevant to the DT, need to share the DT among multiple application systems involving multiple stakeholders and Uncertainties in the quality and reliability of data are the main barriers for adopting digital twins' technology. Moreover, Ginni’s mean difference measure of dispersion showed that the stationary digital twin’s barriers adoption is needed to share the DT among multiple application systems involving multiple stakeholders.

The study’s findings offer valuable guidance to the construction industry. They help stakeholders adopt digital twins' technology, which, in turn, improves cost efficiency and sustainability. This adoption reduces project expenses and enhances environmental responsibility, providing companies a competitive edge in the industry.

This research rigorously explores barriers to Digital Twin (DT) implementation in the Hong Kong construction industry, employing a systematic approach that includes a comprehensive literature review, Ranking Analysis (RII) and Ginni’s coefficient of mean difference (GM). With a tailored focus on Hong Kong, the study aims to identify, analyze and provide novel insights into DT implementation challenges. Emphasizing practical relevance, the research bridges the gap between academic understanding and real-world application, offering actionable solutions for industry professionals, policymakers and researchers. This multifaceted contribution enhances the feasibility and success of DT implementation in construction projects within the Architecture, Engineering and Construction (AEC) sector.

The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.

This study aims to identify the perception of people in a Portuguese company regarding the main barriers to the effectiveness of the existing performance measurement system (PMS) and whether those perceptions are dependent of people’s hierarchical levels, education levels, work shifts, gender and department.

Primary data was collected through structured interviews (adapted to three levels of interviewees in the company hierarchy) and Likert scale questionnaires. Descriptive statistical analysis of the collected data was performed as well as a chi-square test.

The results provide an insight on the perception of barriers to the PMS effectiveness in the company. After performing interviews and questionnaires it was possible to identify that the main perceived barriers were: poor communication system and issues on target definition, lack of trained resources, employee involvement, indicators understanding and use for improvement.

This study is the starting point to develop actions aiming to eliminate, or at least mitigate, the impact of the barriers on the PMS effectiveness.

PMSs play an essential role in an organization, so it is essential to identify what hinders its effectiveness. This study opens the discussion by diagnosing the company’s perception of the barriers to PMS effectiveness.