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The paper aims to identify, prioritize and rank lean practices in the context of an Indian automotive component manufacturing organization using interpretive ranking process (IRP) and interpretive structural modeling (ISM) approaches.

Lean practices are identified from the literature. Then, two hierarchical models were are developed using two distinct modeling approaches – ISM and IRP with expert opinions from an Indian automotive component manufacturing organization to analyze the contextual relationships among the various lean practices and to prioritize and rank them with respect to performance dimensions.

In the study, the hierarchical structural models are developed using ISM and IRP approaches for an Indian automotive component manufacturing organization. In ISM-based modeling, lean practices can be categorized into five levels. Top priority should be given to the motivators followed by value chain, system/technology and organization centric practices. IRP model shows the dominance relationship among the various lean practices with respect to performance dimensions.

The models are constructed from the organizational standpoint to evaluate their impact to the implementation of lean manufacturing. The study leverages the organizations to prioritize limited resources as per the hierarchy. Managers get the inter-linkages and ranking of various lean practices, which leads to a better perspective for the effective implementation of lean. The structural models also assist management to assign proper roles to employees/departments for effective lean implementation.

There is hardly any structural model of lean practices in the literature for clustering, prioritizing and ranking of lean practices. The study fills this gap and develops the hierarchical models of lean practices through IRP and ISM approaches for an Indian automotive component manufacturing organization. The results from both approaches are compared for illustrating the benefits of one over the other.

This study aims to scrutinize the relationship between the perception of big data (BD) features and the primary outcomes of financial accounting. Likewise, it explores whether financial accounting practices moderate the relationship between BD features and firm sustainability.

The study used a questionnaire survey based on the Likert scale for two distinct groups of participants: academic scholars and industry practitioners operating in the BD era within the energy sector.

The results reveal significant positive associations between BD features and firm performance, reporting quality, earnings determinants, fair value measurements, risk management, firm value, the efficiency of the decision-making process, narrative disclosure and firm sustainability. Besides, the path analysis indicates an indirect impact of BD on firm sustainability via financial accounting practices. The results suggest that energy firms should consider incorporating BD analysis into their financial accounting processes to improve their sustainability performance and create long-term value for their stakeholders.

The findings are particularly interesting to academics in accounting and business to improve the accounting curriculums to fit the technological revolution, especially in the field of BD analytics. Practitioners within energy industries must also refine their skills and knowledge to meet the challenges of BD in the foreseeable future. The results provide important implications for policy setters to revise current financial accounting standards to cope with technological innovation.

The study makes a valuable contribution by critically examining the impact of BD on various financial accounting practices neglected in prior research. It highlights the transformative power of BD in the domain of financial accounting and provides insights into its potential implications for energy firms.

With the rapid-growing house market in the past decade, the purpose of this paper is to study the important issue of house price information flows among 12 major cities in China, including Shanghai, Beijing, Xiamen, Shenzhen, Guangzhou, Hangzhou, Ningbo, Nanjing, Zhuhai, Fuzhou, Suzhou and Dongguan, during the period of June 2010 to May 2019.

The authors approach this issue in both time and frequency domains, latter of which is facilitated through wavelet analysis and by exploring both linear and nonlinear causality under the vector autoregressive framework.

The main findings are threefold. First, in the long run of the time domain and for timescales beyond 16 months of the frequency domain, house prices of all cities significantly affect each other. For timescales up to 16 months, linear causality is weaker and is most often identified for the scale of four to eight months. Second, while nonlinear causality is seldom determined in the time domain and is never found for timescales up to four months, it is identified for scales beyond four months and particularly for those beyond 32 months. Third, nonlinear causality found in the frequency domain is partly explained by the volatility spillover effect.

Results here should be of use to policymakers in certain policy analysis.

The main purpose of this research is to (1) prioritise key determinants of Industry 4.0 (I4.0) readiness assessment and (2) evaluate causal relationships among those determinants and associated sub-criteria based on inputs from industry experts.

The methodology involved two phases: (1) an MCDM approach for determining causal relationships among determinants and (2) empirical validation of findings from the first phase using industry experts' inputs.

It was found that while the choice of I4.0 technologies is important, organisational factors are also critical, as evidenced by the ranking of the “Strategy and Organisation” determinant as the highest rank prominent determinant. Also, the ranking of the sub-criteria within each determinant shows the importance of several organisational influencing and resulting sub-criteria.

This research extends the existing literature on I4.0 by demonstrating the prioritisation of determinants and delineating causal relationships among them and associated sub-criteria as a basis for developing I4.0 adoption guidelines. This research is limited to the specific scope of determinants selected/considered and experts' inputs from the Sri Lankan manufacturing sector. Future studies could consider extending this research into a broader global manufacturing context.

Prioritisation and causal relationships of I4.0 readiness assessment determinants, supported with inputs from functional managers and industry experts, could be used to guide practitioners in developing guidelines for I4.0 adoption in a phased manner.

This research provides a re-evaluation and validation of a selected I4.0 readiness assessment framework from the perspectives of interdependencies and casual relationships among its determinants and sub-criteria, based on inputs from industry experts as a basis for developing guidelines for I4.0 adoption.

As newer high performance polymers in mechanical properties become available for material extrusion-based additive manufacturing, determining infill parameter settings becomes more important to achieve both operational and mechanical performance of printed outputs. For the material extrusion of carbon fiber reinforced poly-ether-ether-ketone (CFR-PEEK), this study aims not only to identify the effects of infill parameters on both operational and mechanical performance but also to derive appropriate infill settings through a multicriteria decision-making process considering the conflicting effects.

A full-factorial experimental design to investigate the effects of two major infill parameters (i.e. infill pattern and density) on each performance measure (i.e. printing time, sample mass, energy consumption and maximum tensile load) is separately performed to derive the best infill settings for each measure. Focusing on energy consumption for operational performance and maximum tensile load for mechanical performance, the technique for order preference by similarity to ideal solution is further used to identify the most appropriate infill settings given relative preferences on the conflicting performance measures.

The results show that the honeycomb pattern type with 25% density is consistently identified as the best for the operational performance measures, while the triangular pattern with 100% density is the best for the mechanical performance measure. Moreover, it is suggested that certain ranges of preference weights on operational and mechanical performance can guide the best parameter settings for the overall material extrusion performance of CFR-PEEK.

The findings from this study can help practitioners selectively decide on infill parameters by considering both operational and mechanical aspects and their possible trade-offs.

In the context of promoting sustainable development in SMEs, the present study aims to investigate the relationship among solution dimensions based on the Industry 4.0 (I4.0) concept.

The study employs a comprehensive methodology that includes a systematic literature review, workshop, grounded theory and interpretive structural modeling. Various dimensions concerning I4.0 sustainability are tested and evaluated using a questionnaire design followed by hypothesis formulation. Further, grounded theory is used to extract the key solution dimensions that capture the essence of I4.0 implementation in SMEs. Finally, the solution dimensions for I4.0 sustainability are modeled using the ISM approach to understand the structural interdependencies among them, and Matrice d'Impacts Croisés Multiplication Applied to a Classification (MICMAC) analysis is done to understand the driving and dependence power among these dimensions.

The study identified 14 solution dimensions for the implementation of I4.0 in SMEs for sustainable development. Out of the 14 solution dimensions, human resource training programs (D4) appear at level 11, followed by top management commitment (D1), strategic collaborations (D3) and coordination among key stakeholders (D5) at level 2 in the hierarchical interpretive structural modeling (ISM) model. Also, these dimensions have an effect size of more than 0.50 which indicates a substantial correlation between the sustainability dimensions and Industry 4.0 implementation in SMEs.

The study contributes to the overall goal of fostering sustainability within the SME sector, which can pave the way for various stakeholders for the successful implementation of I4.0 sustainable solution dimensions.

Constructing porous wind barriers is one of the most effective approaches to increase the running safety of trains on viaducts in crosswinds. This paper aims to further improve the wind-sheltering performance of the porous wind barriers.

Improved delayed detached eddy simulations based on the k-ω turbulence model were carried out, and the results were validated with wind tunnel tests. The effects of the hole diameter on the flow characteristics and wind-sheltering performance were studied by comparing the wind barriers with the porosity of 21.6% and the hole diameters of 60 mm–360 mm. The flow characteristics above the windward and leeward tracks were analyzed, and the wind-sheltering performance of the wind barriers was assessed using the wind speed reduction coefficients.

The hole diameters affected the jet behind the wind barriers and the recirculation region above the tracks. Below the top of the wind barriers, the time-averaged velocity first decreased and then increased with the increase in the hole diameter. The wind barrier with the hole diameter of 120 mm had the best wind-sheltering performance for the windward track, but such barrier might lead to overprotection on the leeward track. The wind-sheltering performance of the wind barriers with the hole diameters of 240 mm and 360 mm was significantly degraded, especially above the windward track.

The effects of the hole diameters on the wake and wind-sheltering performance of the wind barriers were studied, by which the theoretical basis is provided for a better design of the porous wind barrier.

A crucial issue in educational management refers to helping teachers reach their full potential and manage their talents. Although managing talent is advised as an essential resource for organizational transformation to maximize performance and to promote a school’s knowledge capital increase, Teachers’ talent management (TTM) is not an agreed-upon concept in the literature. The aim of this study is threefold: (1) to propose a theoretical and operational TTM definition, (2) to develop a test to measure TTM and (3) to discuss the value of TTM implementation in educational settings.

A psychometric validation design according to international standards for test development is implemented. A cross-sectional intentional sampling with 200 schools is used for obtaining reliability and validity evidence. We operationalized TTM using 9 factors (10 items per factor, 6-point Likert scale): attraction, selection, development, retention, succession, climate, culture, evaluation and knowledge management.

Results show adequate evidence of reliability and validity, focusing on items' content and latent structure. The combined use of structural equation models (SEM) and psychometric networks (PN) detects a six-factor model with a test reduced version including 61 items, getting 64.28% of the total explained variance and adequate reliability indices and factor loadings.

The Teachers' Talent Management Assessment Test (TTMAT) can contribute educational institutions to create a culture of excellence and deliver the best possible education to their students. Educational transformation will only happen if teachers are professionalized, trained, motivated and supported to inspire and to guide their learners to reach their objectives and well-being.

Children in majority world countries (MWC) have high rates of unmet mental health needs, with limited access to specialist resources. Integration of child mental health in existing psychosocial care can improve provision. Through a Train-the-Trainer (ToT) cascade approach, this study aimed to provide a framework for such integration in resource-constrained communities in Karachi, Pakistan and to establish hindering and enabling factors.

Eight practitioners attended a child mental health ToT program, including training on a five-domain service transformation framework. Trainers co-designed and implemented interventions that integrated child mental health knowledge and skills on each domain. These were attended by 136 end-users (youth, parents, teachers, managers), of whom a sub-sample of 47 stakeholders, as well as the trainers, attended focus groups on their experiences. Data were analysed through a thematic codebook.

Established themes reflected common ingredients across all domains/interventions that were deemed important for child mental health care integration. These included child-centric approaches, positive parenting, community mobilization and systemic changes.

Integrated child mental health care informed by the Train-of-Trainer approach can be a useful model for resource-constrained MWC contexts. Integrated interventions should be co-produced with communities.

Empowerment is recognised as being a key to achieving organisational agility. Typically associated with a particular leadership style, implications of empowerment for management have remained vague in the literature. Thus, this study aims at unpacking the facets and mechanisms of empowerment in the context of organisational units (OUs).

First, the authors review the extant literature and discuss the crucial concepts in the context empowerment. Then, the authors analyse qualitative data from interviews conducted in four research and development (R&D) departments in the industrial manufacturing industry.

This study finds that the empowerment of business entities is crucial when operating in turbulent conditions. However, empowerment must be accompanied by a clear focus when aiming at higher agile performance. Moreover, different autonomy types and their interplay with critical factors of middle management empowerment could be identified. The research results also reveal important details about the effects of autonomy on motivation and performance and the role of OUs' dependencies.

The model proposed in this paper can help senior and middle managers better manage the empowerment of OUs required to enhance middle management agility and, in turn, increase overall organisational adaptability.

Beyond regarding empowerment as a leadership style, this paper takes a middle management perspective and unfolds the facets of empowerment in the context of OUs. Adding to the theory of self-organisation, a model is proposed to capture the key factors to determine and manage the autonomy of OUs. These insights are essential to managing autonomy successfully at the middle management level.