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Manufacturing firms must embrace smart technologies and develop complex leadership approaches to achieve sustainability. Using the dynamic capability theory, this paper aims to examine the influence of the adoption of industry 4.0 technologies (AT) and paradoxical leadership (PL) on corporate sustainable performance (CSP) of manufacturing small-medium enterprises (SMEs) in Malaysia. Moreover, organisational ambidexterity (OA) is a mediator and strategic flexibility (SF) is a moderator in the study.

The study is a cross-sectional, quantitative study design that collected 395 usable responses through a simple random sampling technique and a close-ended structured questionnaire. Structural equation modelling (SEM) procedures were followed to analyse the data.

The statistical outcome implies that the AT significantly influence CSP and OA and mediate with CSP in the presence of OA. Moreover, PL shows a significant impact on OA, is insignificant on CSP and mediates with OA and CSP. The authors found a significant association between OA and CSP; however, SF did not provide evidence of a moderate effect.

The findings of this study clarify the role that organisational capabilities (OA, AT, PL and SF) play in fostering sustainability. The authors suggest incorporating SMEs from different geographies in other sectors by applying diverse methodologies and relevant constructs.

The result injects new perspectives into policy, managerial and individual levels. Installing OA, AT, PL and SF makes SMEs sustainable.

The empirical validation of the influence of OA and AT on CSP and the interaction of PL and SF enriches the organisational and entrepreneurial literature.

Manufacturing small and medium-sized enterprises (SMEs) are heading towards smart manufacturing despite growing challenges caused by globalisation and rapid technological advancement. These SMEs, particularly textile SMEs of Bangladesh, also face challenges in implementing sustainability and organisational ambidexterity (OA) due to resource constraints and limitations of conventional leadership styles. Adopting paradoxical leadership (PL) and entrepreneurial bricolage (EB) is important to overcome the challenges. However, these dynamics are less explored in academia, especially in the Bangladeshi textile SMEs context. Hence, the purpose of this study is to investigate the influence of the adoption of smart technologies (ASTs), PL and OA, EB on sustainable performance (SP) of textile SMEs in Bangladesh.

A cross-sectional and primary quantitative survey was conducted. Data from 361 textile SMEs were collected using a structured self-administrated questionnaire and analysed by partial least square structural equation modelling (PLS-SEM).

The statistical outcome confirms that ASTs and PL significantly influence SP and OA. OA plays a significant mediating role for PL and is insignificant for ASTs, and EB significantly moderates among ASTs, PL and SP.

As this study is cross-sectional and focussed on a single city (Dhaka, Bangladesh), conducting longitudinal studies and considering other parts of the country can provide exciting findings.

This research provides valuable insights for policymakers, management and textile SMEs in developing and developed countries. By adopting unique and innovative OA, PL and EB approaches, manufacturing SMEs, especially textile companies, can be more sustainable.

This study has a novel, pioneering contribution, as it empirically validates the role of multiple constructs such as AST, PL, OA and EB towards SP in the context of textile SMEs in a developing country like Bangladesh.

This study aims to provide a comprehensive, textometric analysis of the evolving Quality 4.0 (Q4.0) research, identifying key themes, emerging trends and critical research gaps in the field.

A total of 129 peer-reviewed articles on Q4.0 were analyzed using IRAMUTEQ software. The textometric approach employed includes lexicographic analysis, descending hierarchical classification, factorial correspondence analysis and similarity analysis to uncover underlying patterns in the literature.

Three major clusters emerged from the analysis of Q4.0 research: (1) the digital transformation of quality management practices, (2) technological enablers of Q4.0 and (3) organizational implications of Q4.0 adoption. Key themes identified include the integration of Industry 4.0 technologies (e.g. IoT, AI and big data) into traditional quality management systems, the role of artificial intelligence in quality control and the challenges organizations face during Q4.0 implementation. This research also conceptualizes a comprehensive framework that outlines a strategic roadmap for Q4.0 adoption and integration, including the identification of antecedents and consequences of Q4.0 implementation. Additionally, the study proposes a measurement scale for assessing the dimensions of Q4.0.

The research proposes valuable implications for practitioners and organizations seeking to implement Q4.0 strategies as well as for researchers in the field of digital transformation and quality management. The proposed conceptual framework serves as a practical guide for effectively navigating Q4.0 implementation in diverse organizational contexts.

This study presents an innovative approach by applying textometric analysis to the field of Q4.0, offering an objective, data-driven perspective on the existing literature. It identifies significant gaps in research and proposes future avenues for investigation. As one of the first studies to develop a conceptual framework for Q4.0, including its antecedents, consequences and a measurement scale, this research provides a foundational contribution to the growing body of knowledge on Q4.0.

With emerging technologies rapidly changing work processes, it is important to understand the skills and characteristics project managers (PMs) need to effectively manage projects in the digital era. This study determines the underlying competencies needed for digitalization among PMs in the construction industry. The study also identified the most significant competencies needed by PMs in the era of digitalization.

The methodology adopted for the research study was quantitative. It was founded on a thorough review of pertinent literature, which went through a pilot survey study from six project management experts in the construction industry. Based on the comment and feedback, a questionnaire survey was developed and distributed to participants through a convenience sampling technique. The data retrieved were from 100 professional PMs out of 130 questionnaires distributed in the Ghanaian construction industry. Data collected were analyzed using fuzzy synthetic evaluation (FSE).

Based on FSE, the three competency parameters (knowledge, skills, personal characteristics) generated significant indices indicating that all three competencies are significant among construction PMs in the digitalization era. Under the knowledge competency parameter, six sub-competencies comprising a total of 12 variables were identified. For skills, seven sub-competencies consisting of 23 variables were identified. Regarding personal attributes, six sub-competencies with 17 variables were highlighted. Under knowledge, technical knowledge was found to be the most important with an index of 4.212. For skills, leadership skills were rated highest with an index of 4.240. Regarding personal attributes, social or interpersonal skills were deemed most critical with an index of 4.199.

The results provide guidance to both industry and academic stakeholders. For PMs and their employers, the study highlights priority areas for competency development and training related to the era of digitalization. It also informs educational institutions on how to structure project management curricula to best prepare students for jobs of the future. This study gives more insight into the competencies that need more attention for PMs in the digitalization era. As a result, firms that adopt the identified competency will benefit from implementing digitalization in project delivery.

This study makes an original contribution as one of the first to empirically investigate the competencies required of construction PMs in the construction industry in the digitalization era. By focusing on the developing country context of Ghana, the study extends knowledge to an under-researched region and market. It provides a foundation for future comparative research across diverse global contexts.

The purpose of this paper is to explore the approaches to education and training adopted by manufacturing organisations to identify and develop a set of learning principles for the successful transition to Industry 4.0.

A case study of a manufacturing ecosystem in Queensland, Australia was undertaken, that included semi-structured interviews with a total sample of 22 manufacturing industry representatives, an analysis of secondary data including organisational documents and government reports, and embedded cases of two manufacturing organisations.

Manufacturers successfully transitioning to Industry 4.0 are distinguished by a culture which values learning, management development to understand and lead innovation, experimental learning on the job and strong links to education and training providers through internships and upskilling pathways. These four principles inform approaches to creating tailored training solutions that respond to the unique needs of diverse manufacturing organisations.

The two case studies describe exemplary high performing companies only and not companies at earlier stages of adopting Industry 4.0. Therefore, future research could include a broader spectrum of companies across the adoption spectrum. Nevertheless, considered as a study of a total manufacturing ecosystem, there is strong alignment of views of government, industry, union and education stakeholders regarding the key factors of transition to Industry 4.0.

There is a strong need for leaders of manufacturing organisations to enable a broad strategy of capability development beyond simple acquisition of new technologies. Detailed consideration and resourcing of on-the-job training and experimentation, talent attraction through innovation workplace cultures and strong relationships with education providers are important.

Given that Industry 4.0 technologies such as robotics and AI are now rapidly diffusing into other industry sectors, the research has broader implications for education and training for the future of work. These technologies could produce stark differences between efficiency versus innovation-oriented adoption strategies. Whilst the former could displace workers, the latter can open pathways for upskilling, product and process innovation and cross sector employment.

Through the ecosystem level case approach, multiple stakeholder perspectives provide triangulated insights into advanced manufacturer's education, skills and training strategies, uncovering four learning principles that underpin the approach of manufacturers successfully transitioning to Industry 4.0. The findings have practical implications for policy makers and industry bodies supporting the transition to advanced manufacturing and provide manufacturing managers with insights into successful education and skill strategies that can be adapted to specific organisational needs.

This study investigates the enablers and challenges of digital supply chains (DSCs) adoption and develops a digital supply chain maturity (DSCM) model as a basis for developing guidelines for DSC adoption in the digital transformation journey.

The research involves a systematic literature review (SLR) of Industry 4.0 (I4) adoption in supply chain (SC) practices to identify key enablers and associated maturity levels. The literature search of published articles during the 1997–2020 period and subsequent screening resulted in 64 articles. A DSCM model was developed using the categorization of important enablers and associated levels transitioning from the traditional SC to the DSC ecosystem.

Four broader categories of DSC enablers and challenges were identified from the content analysis of SLR. Digital strategy alongside I4 technologies and human capital were prominent in DSC adoption as I4 technologies and human capital depend on other enablers such as dynamic capabilities (DCs). Lack of infrastructure and financial constraints to implementing I4 were significant challenges in the DSC adoption.

The proposed DSCM model provides a holistic view of enablers and maturity levels from traditional SC to DSC adoption. However, the DSCM model needs to be empirically validated and streamlined further using inputs from practitioners.

The proposed DSCM model can be used as a framework to guide practitioners in assessing maturity and developing implementation plans for successful DSC adoption.

This research introduces a novel DSC maturity model through a holistic view of enablers and maturity levels from traditional SC to DSC adoption.

The purpose is to assess Industry 4.0 (I4.0) readiness index using fuzzy logic and multi-grade fuzzy approaches in an automotive component manufacturing organization.

I4.0 implies fourth industrial revolution that necessitates vital challenges to be dealt with. In this viewpoint, this article presents the evaluation of I4.0 Readiness Index. The evaluation includes two levels with appropriate criteria and factors. Fuzzy logic approach is used for assessment. Furthermore, the results obtained from fuzzy logic have been benchmarked with multi-grade fuzzy approach.

The proposed assessment model has successfully utilized fuzzy logic approach for assessment of I4.0 readiness index of automotive component manufacturing organization. Based on fuzzy logic approach, readiness index of I4.0 has been found to be (4.74, 6.26, 7.80) which is further benchmarked using multi-grade fuzzy approach. Industry 4.0 readiness index obtained from multi-grade fuzzy approach is 6.258 and thus, validated. Furthermore, 20 weaker areas have been identified and improvement suggestions are provided.

The assessment module include two levels (Six Criteria and 50 Factors). The assessment model could be expanded based on advancements in industrial developments. Therefore, future researchers could utilize findings of the readiness model to further develop multi-level assessment module for Industry 4.0 readiness in organization. The developed readiness model helped researchers in understanding the methodology to assess I4.0 readiness of organization.

The model has been tested with reference to automotive component manufacturing organization and hence the inferences derived have practical relevance. Furthermore, the benchmarking strategy adopted in the present study is simple to understand that makes the model unique and could be applied to other organizations. The results obtained from the study reveal that fuzzy logic-based readiness model is efficient to assess I4.0 readiness of industry.

The development of model for I4.0 readiness assessment and further analysis is the original contribution of the authors. The developed fuzzy logic based I4.0 readiness model indicated the readiness level of an organization using I4RI. Also, the model provided weaker areas based on FPII values which is essential to improve the readiness of organization that already began with the adoption of I4.0 concepts. Further modification in the readiness model would help in enhancing I4.0 readiness of organization. Moreover, the benchmarking strategy adopted in the study i.e. MGF would help to validate the computed I4.0 readiness.

The purpose of this research paper is to study the significant enablers for a competitive supply chain and analyze the relationships among them by using multi-criteria decision-making (MCDM) techniques. The supply chain (SC) managers will get better insights from the models of this study to design their SCs that are more competitive for competitive advantage.

After an extensive review of literature followed by experts' opinions, 21 significant enablers for a competitive SC (CSC) were selected for structural modeling using MCDM techniques of total interpretive structural modeling (TISM), Impact Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC), followed by decision-making trial and evaluation laboratory (DEMATEL) approach.

Top management commitment is the most prominent causing enabler of a CSC; customer satisfaction is the topmost effect enabler; the operational performance of individual firms in the supply chain is a crucial enabler of a CSC.

The results and findings of this study would provide better insights to SC professionals and practitioners to comprehend the significant enablers of a CSC for designing and executing SC operations more competitively to achieve better customer satisfaction and sustainable business performance.

To the best of the authors’ knowledge, this is a foremost study focusing on the significant enablers of a CSC by utilizing the TISM along with MICMAC and DEMATEL methods. It is expected that this research will offer useful guidance for assessing and considering the SC enablers for achieving a CSC and facilitate new research in this area with more thrust.

Industry 4.0 is the present trend in automation and data exchange in organizations. However, till today, there is no generic and common understanding in terms of assessing the Industry 4.0 readiness for organizations. The purpose of this paper is to identify the key ingredients for assessing Industry 4.0 readiness for organizations, the interrelationships that exist between these readiness factors and how future research should proceed given the research findings.

A systematic literature review (SLR) methodology of Tranfield et al. (2003) was employed to ensure the replicability and transparency of the review process. Altogether, 68 articles were identified for the final thematic analysis.

The SLR results generated six broad themes of readiness factors. The interrelationship mechanism between these factors was identified. In addition, 17 research propositions were elucidated.

Being the first literature review on assessing Industry 4.0 readiness for organizations, it finds 17 research propositions which will give the future researchers a guideline for further research in Industry 4.0.

Although Industry 4.0 is the buzzword, very few organizations understand the concept in detail. This paper will help the organizations to identify the factors which they have to asses critically before implementing Industry 4.0 in an organization.

Nevertheless, there has been a lot of research on Industry 4.0; this is the first systematic literature to identify the key ingredients for assessing Industry 4.0 readiness for organizations.

New acrylic and allylic resins were prepared by functionalising perfluoropolyethers chains, which assured peculiar surface properties. Blends having a different amount of the acrylic and of the allylic systems were cured in air by UV irradiation. The cure of the films was found dependent on the ratio between the two resins; the concentration for the obtaining of a film fully cured in air was determined. On the basis of this concentration, a macromer functionalised with the right amount of both the acrylic group and the allylic one was synthesised.