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This study investigates the optimum size for manufacturing firms and the impact of subcontracting on firms' likelihood of achieving their optimal scale in Vietnam.

Using data from the enterprise census in 2017 and 2021, the paper first estimates the production function to identify the optimum firm size for manufacturing firms and then, applies the logit model to investigate factors associated with the optimal firm size.

The study reveals that medium-sized firms exhibit the highest level of productivity. Nevertheless, a consistent trend emerges, indicating that nearly 90% of manufacturing firms in Vietnam operated below their optimal scale in both 2017 and 2021. An analysis of the impact of subcontracting on firms' likelihood to achieve their optimal scale emphasizes its crucial role, especially for foreign firms, exerting an influence nearly five times greater than that of the judiciary system.

The paper's findings offer crucial policy implications, suggesting that initiatives aimed at enhancing the overall productivity of the manufacturing sector should prioritise facilitating contract arrangements to encourage firms to reach their optimal size. These insights are also valuable for other countries with comparable firm size distributions.

This paper provides the first empirical evidence on the relationship between firm size and productivity as well as the role of subcontracting in firms' ability to reach their optimal scale in a country with a right-skewed distribution of firm sizes.

Spare Parts Management (SPM) and Industry 4.0 has proven their importance. However, employment of Industry 4.0 solutions for SPM is at emerging stage. To address the issue, this article is aimed toward a systematic literature review on SPM in Industry 4.0 era and identification of research gaps in the field with prospects.

Research articles were reviewed and analyzed through a content-based analysis using four step process model. The proposed framework consists of five categories such as Inventory Management, Types of Spares, Circularity based on 6Rs, Performance Indicators and Strategic and Operational. Based on these categories, a total of 118 research articles published between 1998 and 2022 were reviewed.

The technological solutions of Industry 4.0 concepts have provided numerous opportunities for SPM. Industry 4.0 hi-tech solutions can enhance agility, operational efficiency, quality of product and service, customer satisfaction, sustainability and profitability.

The review of articles provides an integrated framework which recognizes implementation issues and challenges in the field. The proposed framework will support academia and practitioners toward implementation of technological solutions of Industry 4.0 in SPM. Implementation of Industry 4.0 in SPM may help in improving the triple bottom line aspect of sustainability which can make significant contribution to academia, practitioners and society.

The examination uncovered a scarcity of research in the intersection of SPM and Industry 4.0 concepts, suggesting a significant opportunity for additional investigative efforts.

The paper aims to propose and validate a process-based model to enhance managerial effectiveness among micro, small and medium enterprises (MSMEs). It has been observed that business uncertainties and inadequate financial resources that MSME entrepreneurs and managers face require them to constantly engage in strong self-awareness and self-regulating behavior to enhance the efficacy in their roles and, henceforth, their role performance effectiveness.

The approach for data collection was based on the clustering of MSMEs belonging to the clusters machine tool, pump manufacturing, foundry, textile and auto-component clusters in India. The respondents to the study were MSME entrepreneurs and managers who oversee and manage multiple functions like operations, quality, marketing, sales, supply chain management, procurement, personnel and administration and general administration.

The self-efficacy of entrepreneurial managers of MSMEs is observed to play an integral role in enhancing the efficacy of their roles, thus highlighting the use of a process-based perspective while dealing with constant resource constraints and excessive dynamism in their business contexts. The ability to handle multiple tasks effectively and resilience to manage challenges enhances their role-making process, which is significant in achieving and sustaining goal-oriented behavior among MSME entrepreneurs and managers.

This paper would serve as an effective model for entrepreneurs and managers to enhance their efficacy in the individual and interdependent role context, which would help achieve their individual and organizational goals. The model emphasizes a process-based perspective that thrusts the need to relate to the organizational context, enhancing individual confidence for goal-related behavior and fulfilling their role-related expectations.

This paper presents a model of enhancing managerial effectiveness that discusses self-efficacy as antecedent behavior. Here, personal and environmental factors aid cognition to one’s capability to construct reality, self-regulate, encode information and engage in effective managerial action.

The application of lean and quality improvement methods is very common in process improvement projects at organisational levels. The purpose of this research is to assess the adoption of Lean Six Sigma™ approaches for addressing a complex process-related issue in the coal industry.

The sticky coal problem was investigated from the perspective of process-related issues. Issues were addressed using a blended Lean value stream of supply chain interfaces and waste minimisation through the Six Sigma™ DMAIC problem-solving approach, taking into consideration cross-organisational processes.

It was found that the tendency to “solve the problem” at the receiving location without communication to the upstream was, and is still, a common practice that led to the main problem of downstream issues. The application of DMAIC Six Sigma™ helped to address the broader problem. The overall operations were improved significantly, showing the reduction of sticky coal/wagon hang-up in the downstream coal handling terminal.

The Lean Six Sigma approaches were adopted using DMAIC across cross-organisational supply chain processes. However, blending Lean and Six Sigma methods needs to be empirically tested across other sectors.

The proposed methodology, using a framework of Lean Six Sigma approaches, could be used to guide practitioners in addressing similar complex and recurring issues in the manufacturing sector.

This research introduces a novel approach to process analysis, selection and contextualised improvement using a combination of Lean Six Sigma™ tools, techniques and methodologies sustained within a supply chain with certified ISO 9001 quality management systems.

Drawing upon a systematic literature review in new technology, innovation transfer and diffusion theories, and from interviews with technology leaders in digital transformation programs in the US Oil & Gas (O&G) industry, the authors explore the relationships among O&G industry dynamics, organization's absorptive capacity and resource commitment for new digital technology adoption-implementation process.

The authors employed the empirical survey method to gather the data (a sample size of 172) in the US O&G industry and used structural equation modeling (SEM) to test the measurement model for validity and reliability and the conceptual model for hypothesized structural relationships.

The results provide support for the study’s causal model of adoption and implementation with positive and direct relationships between the initiation and trial stages, between the trial stages and the evaluation of effective outcomes and between the effective outcomes and the effective implementation stages of digital technologies. The results also reveal partial mediating relationships of industry dynamics, absorptive capacity and resource commitment between respective stages.

Based on the current study's findings, managers are recommended to pay attention to the evolving industry dynamics during the initiation stage of new digital technology adoption, to utilize the organization's knowledge-based absorptive capacity during digital technology trial and selection stages and to support the digital technology implementation project when the adoption decision of a particular digital technology has been made.

The empirical research contributes literature on digital technology adoption and implementation by identifying and demonstrating the importance of industry dynamics, absorptive capacity and resource commitment factors as mediating variables at various stages of the adoption-implementation process and empirically validating a process-based causal model of digital technology adoption and a successful implementation project that has been missing in the current body of literature on digital transformation.

The purpose of this paper is to develop a framework to facilitate early supplier involvement (ESI) as an approach for reducing construction waste (CW) generated during the design process.

A research methodology consists of literature review, case studies and survey questionnaire was designed to achieve the abovementioned aim. First, the literature review was used to investigate CW, CW generated during the design process, the design process and ESI. Second, two construction projects were analysed to investigate the role of ESI towards reducing CW generated during the design waste. Third, a survey questionnaire was carried out with a representative sample of architectural design firms (ADFs) in Egypt to examine their perception and application of ESI towards reducing CW generated during the design process. Based on the results of the above, the research developed a framework to facilitate ESI during the design process to reduce CW.

Through literature review, the research highlighted the causes of CW generated during the design process and identified the benefits and challenges that encounter ESI in ADFs. Results of data analysis showed that “last-minute changes due to client requirements” was ranked the highest challenges of ESI in ADFs in Egypt followed by “lack of design experience”. Moreover, “providing technical information about materials and equipment and their capabilities” was ranked by respondents as the highest contributions of suppliers during the design process which leads to waste reduction followed by “better estimation of materials and costs”. Finally, respondents stated that “resistance of ADFs to include suppliers in the design phase” was ranked the highest challenge of ESI in the design process followed by “no clear guidelines or policies that organise ESI”.

Because of the conceptual nature of the proposed framework, it has to be tested and validated to ensure its capability to overcome the challenges of ESI as an approach for reducing CW generated during the design process.

This research presents a practical solution to the problem of CW generated during the design process through ESI.

The research discussed the causes of CW originated from the design process and the benefits and challenges of ESI in ADFs. It investigated the perception and application of ESI in ADFs in Egypt. The proposed framework which was designed to facilitate the integration of suppliers in the early stages of the project life cycle represents a synthesis that is novel and creative in thought and adds value to the knowledge in a manner that has not previously occurred.

Digital transformation using Industry 4.0 technologies can address various challenges in food supply chains (FSCs). However, the integration of emerging technologies to achieve digital transformation in FSCs is unclear. This study aims to establish how the digital transformation of FSCs can be achieved by adopting key technologies such as the Internet of Things (IoTs), cloud computing (CC) and big data analytics (BDA).

A systematic literature review (SLR) resulted in 57 articles from 2008 to 2022. Following descriptive and thematic analysis, a conceptual framework based on the diffusion of innovation (DOI) theory and the context-intervention-mechanism-outcome (CIMO) logic is established, along with avenues for future research.

The combination of DOI theory and CIMO logic provides the theoretical foundation for linking the general innovation process to the digital transformation process. A novel conceptual framework for achieving digital transformation in FSCs is developed from the initiation to implementation phases. Objectives and principles for digitally transforming FSCs are identified for the initiation phase. A four-layer technology implementation architecture is developed for the implementation phase, facilitating multiple applications for FSC digital transformation.

The study contributes to the development of theory on digital transformation in FSCs and offers managerial guidelines for accelerating the growth of the food industry using key Industry 4.0 emerging technologies. The proposed framework brings clarity into the “neglected” intermediate stage of data management between data collection and analysis. The study highlights the need for a balanced integration of IoT, CC and BDA as key Industry 4.0 technologies to achieve digital transformation successfully.

The literature on help-seeking at work has experienced significant growth in the past decades. However, our knowledge about this research domain remains fragmented and lacks sufficient theoretical integration. Therefore, this paper aims to comprehensively integrate the extant literature on help-seeking behavior at work and propose an overarching, organized framework to propel this field forward.

A state-of-the-art review and theoretical development on help-seeking at work are conducted.

First, the authors provide the conceptual clarity of its definitions, key characteristics, types and measurement techniques. Second, the authors develop a fine-grained and integrative process-based framework consisting of antecedents, proximal psychological mechanisms, subsequent influencing processes and distal outcomes to advance our understanding of seeking help in the workplace. Third, the authors offer a detailed agenda for future research to target opportunities within the field.

The current study is comprehensive in surveying the full body of knowledge on help-seeking at work. It uniquely provides a coherent overarching framework that organizes prior findings and channels future research. Additionally, this review paints a complete picture of what has been done and what needs to be done in the field. More research can be spurred based on our conceptual framework.

This article aims to explore how cluster affiliation moderates the relationship between family involvement and speed of internationalization in family firms. The speed of internationalization is examined in terms of earliness and post-internationalization speed.

The research is based on a sample of 639 Portuguese family businesses (FBs) created and internationalized between 2010 and 2018 that was retrieved from the Iberian Balance Analysis System – SABI database. The partial least squares structural equation modeling (PLS-SEM) was used to assess the measurement and construct the model.

The results suggest that higher levels of family involvement in ownership and management make family firms enter on international markets in later stages of their development but, after the first international market entry, the firms are able to exhibit a higher post-internationalization speed. When considering the effect of cluster affiliation, the authors found that clustered FBs are more likely to engage in early internationalization and to accelerate the post-internationalization process than non-clustered FBs.

The study's findings are explained by the existence of socially proximate relationships with other cluster members, based on similarity, trust, knowledge exchange and sense of belonging, which push family firms to internationalize and increase their level of international commitment over time. The empirical evidence, therefore, highlights the primary role of industrial clusters in moderating the relationship between family involvement, earliness of internationalization and post-internationalization speed.

The textile industry holds immense significance in the economy of any nation, particularly in the production of synthetic yarn and fabrics. Consequently, the pursuit of acquiring high-quality products at a reduced cost has become a significant concern for countries. The primary objective of this research is to leverage data mining and data intelligence techniques to enhance and refine the production process of texturized yarn by developing an intelligent operating guide that enables the adjustment of production process parameters in the texturized yarn manufacturing process, based on the specifications of raw materials.

This research undertook a systematic literature review to explore the various factors that influence yarn quality. Data mining techniques, including deep learning, K-nearest neighbor (KNN), decision tree, Naïve Bayes, support vector machine and VOTE, were employed to identify the most crucial factors. Subsequently, an executive and dynamic guide was developed utilizing data intelligence tools such as Power BI (Business Intelligence). The proposed model was then applied to the production process of a textile company in Iran 2020 to 2021.

The results of this research highlight that the production process parameters exert a more significant influence on texturized yarn quality than the characteristics of raw materials. The executive production guide was designed by selecting the optimal combination of production process parameters, namely draw ratio, D/Y and primary temperature, with the incorporation of limiting indexes derived from the raw material characteristics to predict tenacity and elongation.

This paper contributes by introducing a novel method for creating a dynamic guide. An intelligent and dynamic guide for tenacity and elongation in texturized yarn production was proposed, boasting an approximate accuracy rate of 80%. This developed guide is dynamic and seamlessly integrated with the production database. It undergoes regular updates every three months, incorporating the selected features of the process and raw materials, their respective thresholds, and the predicted levels of elongation and tenacity.