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The purpose of this paper is to identify the non-value-adding activities (NVAs) of core making process and to eliminate them through the standardization-of-work (SW) procedures in a manufacturing company.

The action-research methodology was adopted for the current study. First, various lean tools were identified through literature review, and the bottleneck area was identified in discussion with the shop-floor executives. NVAs were recorded after a continuous process study including method study and motion analysis followed by the standard operating procedure. Second, the standardized work combination tables were prepared and NVAs were eliminated using the SW procedures. SW has been opted because it is a set of actions which helps in analyzing, improving and controlling the process and it leads to continual improvement.

The production logbook revealed that the capacity in this particular workstation was 54 pieces per 7 h work shift against the current production of approx. 45–50 pieces (past data). SW saved 31.6 s per cycle which boosted the production up to 58 pieces per 7 h work shift. Finally, the authors came to know that the productivity of this particular process increased up to 6.5 percent which may upsurge if this action is executed continually with the support from shop-floor executives and management. These results were also compared with previous research works in this area and found significant relevance, and hence, the results appear to be reliable.

This is a unique study in itself which explores the lean model by assessing NVAs of core making process. The proposed approach needs to be tested across different other core making processes of the case company so as to generalize the effectiveness of SW as well as the results obtained in the current study.

The current study illustrates an important step to give more visibility to the lean concept by addressing the problem of lack of standard procedures. This study will help the shop-floor executives and managers to focus their efforts in achieving high performance through effective implementation of SW. The study should be of the interest of researchers in the area of lean manufacturing, operations management, productivity analysis, etc.

The findings of this study are based on the problem formulation for productivity gains using SW procedures in the case company. The study introduces a new perspective for the execution of SW for core making processes. SW created transparency in workflow, enhanced the safety and eliminated the 3Ms. The outcome of the current study was discussed with the production team and management of the company to validate the productivity gains and received an optimistic response. Most importantly, these improvements were achieved with no investment in machinery or tooling.

This paper examines the mediating role of manufacturing strategies in the relationship between competitive strategies and firm performance.

This study gathered 250 responses from firms in a developing country's key manufacturing sectors, including mechanical, electronics, automotive, textile and food. First, descriptive statistics were applied to fix outliers like respondent biases, missing values and normality issues. Second, exploratory factors analysis (EFA) ensured data adequacy and homogeneity through Kaiser–Meyer–Olkin (KMO) and Bartlett tests. Finally, confirmatory factors analysis (CFA) was used to identify the interactions (direct, indirect and total effects) between latent variables representing manufacturing strategies (quality, cost, delivery and flexibility), competitive strategies (cost-leadership and differentiation) and firms' performance (sales growth and profitability). In total, two structural equation modelling (SEM) models (SEM-I, SEM-II) were created to test the hypotheses.

Of the 40 items identified by the literature review, four were outliers, and three could not satisfy the EFA criteria (eigenvalue >1). Only 33 items could therefore reach CFA. SEM–I and SEM-II study results found no direct relationship between competitive strategies and firm performance (−0.03 = β = 0.08; p > 0.05). However, the findings revealed that cost-leadership could be an appropriate strategic choice and improved firms' performance if the quality and delivery are focussed (0.20 = β = 0.87; p < 0.001). While competitive strategies impact manufacturing strategies positively, the latter is only a mediator between the cost-leadership strategy and the firms' performance.

This research shows that the cost-leadership approach currently seems viable; however, flexibility and cost requirements were not satisfied due to infeasible product differentiation. These results will be beneficial to executives interested in investing in India's industries.

The purpose of this paper is to explore the key performance indicators (PIs) that serve as a decision support tool in case of dairy supply chain practices and to analyze their interactions in the context of Indian dairy industry sector. A total of 11 PIs have been identified through the literature review and the opinions of an expert team consisting of managerial and technical experts from dairy industry and academics.

A solution methodology based on the interpretive structure modeling (ISM) technique is used to analyze the interactions among PIs and to propose a structural model. The developed model not only helps in understanding the contextual relationship among the PIs, but also in determining their interdependence to assess the supply chain performance in dairy industry. Further, the importance of PIs has been determined based on their driving and dependence power by using MICMAC analysis.

The ISM-based model suggests four PIs at first level, three PIs at second level, one PI at third level as well as one PI at fourth level and two PIs at fifth level. Model allocates to the effective information technology, brand management, responsiveness in shipment and accuracy and a control over wastages as the key PIs in the dairy industry sector. The effective traceability systems, cold chain infrastructure, quality management and the support for technological innovations are the next major PIs. There exists no autonomous PI in MICMAC analysis which proves the importance of identified PIs in the case study.

The proposed model is an attempt to capture the dynamics of milk processing sector and to incorporate all relevant constraints related to internal and external environments that would significantly improve the supply chain performance in the dairy industry.

The model developed in this study has been tested in the cooperative milk processing units based in India and also discussed with the experts from academics. This work may help practitioners, regulators and dairy industry professionals to focus their efforts toward achieving high performance by the effective implementation of the identified PIs.

In this study, 11 PIs are considered. Interactions among PIs are evaluated with the help of the ISM matrix. Out of the 11 PIs, six demonstrate both strong driving and dependence power as explained in the MICMAC analysis.

In this global digital era, health-care companies are increasing their presence on the internet through branded content that serves as a connecting link between customers and brands. However, there is a limited understanding of branded content’s impact on customers. Thus, this paper aims to empirically analyse customer engagement for branded content in the health-care sector.

The factors impacting customer engagement for branded content were identified and analysed using the Decision-Making Trial and Evaluation Laboratory approach to get their significance and the cause and effect relationship.

It emerged that co-creation is the most significant factor, having a substantial relationship with all other factors. It is substantiated that health-care companies can increase the intensity of customer engagement by delivering more authentic and relevant content and having an appealing look in a time-bound manner. This will increase the usefulness and entertaining value of the content.

The research findings contribute to the customer engagement dimension in the health-care sector and help the companies construct effective branded content leading towards higher customer engagement.

This study aims to examine the impact of Covid-19 on social and eco-environmental sustainability. It will also investigate the effect of advanced technologies in the post-pandemic era.

To get the robust findings, GMM (Generalized Method of Moments) modeling is employed on the panel data of 50 countries across the globe.

The outcomes indicate that gross fixed capital, logistical operations, knowledge spillover are positive, while Covid-19 is negatively associated with international trade. The results also revealed that Covid-19 spurs poverty and vulnerable employment, while the fertility rate increase creates pressure on economic growth. Also, fossil fuel and energy consumption contribute to carbon emission, while green and advanced technologies may mitigate the environment's adverse effects.

This study is the first of its kind to provide a solution to the challenges posed by the Covid-19 pandemic in the post-pandemic environment. Furthermore, researchers, managers and legislators can use this article's findings to formulate relevant policies for post-pandemic.

Improved production with quality, safety, and security is the biggest challenge of the food industry. Modern technologies, including robotics and automation systems, can help to cope with such issues. This chapter gives a brief view of robotics and automation for the sustainable food industry along with packaging, warehousing, distribution, marketing, and consumer services. It describes the recently implemented solutions of robotic automation in different supply chain operations and various food commodities. The benefits of robotic and automation technology for perishable and semi-perishable items have also been covered. The present research may assist the food industry professionals, supply chain managers, and academicians in implementing automation and robotics in the food industry.

This paper aims to explore the last-mile (LM) challenges faced by on-demand food delivery (ODFD) riders during the coronavirus pandemic. This study contributes to the literature on the less-explored domain of ODFD services.

A grounded theory methodology is used. Riders working for multiple ODFD firms in various urban and semi-urban areas of India were interviewed. Open, axial and selective coding of interview transcripts was done.

A grounded model is developed consisting of riders' challenges represented broadly under four core categories: Operational, Customer-related, Organisational and Technological issues. The study indicates that while some of the challenges are inherent to the ODFD supply chain, these have been visibly exposed and intensified by COVID-19, while other challenges are specific to the pandemic.

The model is a qualitative proposition representing LM delivery issues in ODFD services faced by the riders in India's urban and semi-urban areas during the COVID-19 pandemic. Other countries may face similar problems, but further studies are necessary to confirm or refute the findings.

ODFD companies must address the riders' issues to better adapt to the current and future disruptions and improve riders' quality of work–life to achieve operational excellence.

This study builds on the extant ODFD literature by focusing on one of its less addressed aspects: the working conditions of the riders. This work is conducted amid the COVID-19 pandemic in the context of a developing country and aims to study the challenges in ODFD operations.

Blockchain technology (BCT) has emerged as a powerful tool for enhancing transparency and trust. However, the relationship between the benefits of BCT and agri-food supply chain performance (AFSCperf) remains underexplored. Therefore, the current study investigates the influence of BCT on AFSCperf and sustainability issues.

Through a comprehensive literature review, various benefits of BCT are identified. Subsequently, a research framework is proposed based on data collected from questionnaire surveys and personal visits to professionals in the agri-food industry. The proposed framework is validated using partial least square structural equation modelling (PLS-SEM).

The findings reveal that BCT positively impacts AFSCperf by improving traceability, transparency, food safety and quality, immutability and trust. Additionally, BCT adoption enhances stakeholder collaboration, provides a decentralised network, improves data accessibility and yields a better return on investment, resulting in the overall improvement in AFSCperf and socio-economic sustainability.

This study offers valuable practical insights for practitioners and academicians, establishing empirical links between the benefits of BCT and AFSCperf and providing a deeper understanding of BCT adoption.

Stakeholders, managers, policymakers and technology providers can leverage these findings to optimise the benefits of BCT in enhancing AFSCperf. Moreover, it utilises rigorous theoretical and empirical approaches, drawing on a multidisciplinary perspective encompassing food operations and supply chain literature, public policy, information technology, strategy, organisational theory and sustainability.

The purpose of this paper is to examine the cost leadership competitive strategy’s (CLCS) impact on firm performances and the mediating role of quality management (QM) practices in the context of micro, small and medium enterprises (MSMEs).

A structures questionnaire data collected from 245 ISO 9000 certified MSMEs in India (65.1 per cent of response rate) have been utilised to understand the CLCS’s impact on firm performances. In the first step, the data adequacy tests were performed to check the reliability and validity of the questionnaire and survey data. After that, the partial mediating model (direct, indirect and total effect) along with structural equation modelling approach was employed to test the research hypotheses.

The study results revealed that no direct relationship exists between the CLCS and firm performances (0.12<β<0.13; p>0.05); however, QM practices entirely mediated their relationship (β=0.73, p<0.01). Among eight model parameters, with highest total effects on product quality improvement (β=0.6264) and process improvement (β=0.6028), the continuous improvement secured the rank 1, followed by information and analysis (β=0.2334) and supplier management (0.1839), respectively, at p<0.05. Based on the empirical results, it can be concluded that the continuous improvement via proper information and data analysis is the key to achieve CLCS’s goal in the MSMEs.

The study results’ generalisation towards the large organisations is limited. The survey result findings applicability to other developing countries should also be treated with caution because the Indian Government subsidised the MSMEs selected for this study. The study results will help managers in implementing CLCS at the organisational level. The successful implementation will facilitate a competitive advantage in the local market and will motivate them to think globally.

The research observation and findings are expected to contribute to the strategic management in manufacturing industries. The study also confirms the existence of strategic management in MSMEs in a developing country. Furthermore, the major contribution is to understand the mediating role of QM practices, especially continuous improvement effect on the relationship between CLCS and firm performances in a developing country. The results indicated that the CLCS is only possible when the managers in the manufacturing sectors emphasis on the QM practices in their firms.