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The literature review of post-harvest supply chain (PHSC) losses is carried out and analyzed in this paper followed by bibliometric analysis of the literature.

The literature survey is performed across various dimensions such as PHSC losses, PHSC risks and PHSC sustainability (waste management and waste reduction). One hundred thirty research articles during the period of 1989–2020 were considered for the review.

The PHSC losses have been identified in this literature survey. The calculation and mitigation strategies stated by various researchers in the literature are addressed. The important loss mitigation dynamics are also presented to reduce the PHSC losses and to improve food availability.

The major focus is given on the PHSC of agriculture produces. However, research articles from fish and meat supply chain are excluded as they follow a different perishability curve.

The current work will add value to the agriculture supply chain literature, provide a platform for PHSC losses and provide assistance/guideline toward loss calculation, loss mitigation, improved rural employability, improved rural entrepreneurship and improved revenue generation.

The performed research will assist the researchers, entrepreneurs and farmers to understand the current scenario of food wastage at different stages of the supply chain better. It will provide the guidelines for calculation and mitigation of various stated PHSC losses. This study will be helpful to enhance food availability and food security in post-coronavirus crisis.

The paper explores and highlights PHSC loss calculations and mitigation strategies to identify the postharvest loss situation and better utilization of fresh produces.

The purpose of this study is to select the appropriate forecasting model at the retail stage for selected vegetables on the basis of performance analysis.

Various forecasting models such as the Box–Jenkins-based auto-regressive integrated moving average model and machine learning-based algorithms such as long short-term memory (LSTM) networks, support vector regression (SVR), random forest regression, gradient boosting regression (GBR) and extreme GBR (XGBoost/XGBR) were proposed and applied (i.e. modeling, training, testing and predicting) at the retail stage for selected vegetables to forecast demand. The performance analysis (i.e. forecasting error analysis) was carried out to select the appropriate forecasting model at the retail stage for selected vegetables.

From the obtained results for a case environment, it was observed that the machine learning algorithms, namely LSTM and SVR, produced the better results in comparison with other different demand forecasting models.

The results obtained from the case environment cannot be generalized. However, it may be used for forecasting of different agriculture produces at the retail stage, capturing their demand environment.

The implementation of LSTM and SVR for the case situation at the retail stage will reduce the forecast error, daily retail inventory and fresh produce wastage and will increase the daily revenue.

The demand forecasting model selection for agriculture produce at the retail stage on the basis of performance analysis is a unique study where both traditional and non-traditional models were analyzed and compared.

The purpose of this study is to analyze the post-harvest supply chain enablers (PHSCEs) for vertical integration to enhance rural employability, farmer profitability and rural produce marketability (i.e. market prospects) in the post-harvest supply chain (PHSC). The impact of vertical integration is also explored for various commercial produces.

A structural equation modeling (SEM) of PHSCEs for vertical integration was developed to enhance market prospects, rural employability and farmer profitability. The impact of business-to-business (B2B) and business-to-customer market prospects are explored in various dimensions for stakeholders such as farmers, manufacturers (processors), distributors and retailers. The fuzzy technique for order of preference by similarity to ideal solution (F-TOPSIS) was used to prioritize these PHSCEs to improve market prospects and rural employability.

The PHSCEs are clustered into three groups, namely, initiatives at the strategic frontier, initiatives at the tactical frontier and concerns for rural employability via vertical integration using exploratory factor analysis, confirmatory factor analysis and SEM to prove the null hypothesis. With F-TOPSIS results, the availability of warehousing was found to be the most crucial enabler when observing the PHSCEs from the initiatives’ perspective. The technology adaptability and availability, institute for training and research and information infrastructure and information visibility were found to be the key PHSCEs when observed from PHSC stakeholders’ perspectives.

The implementation of this study will improve the rural produce marketability, rural employability, B2B marketing (i.e. effective distribution) and subsequent value chains with the practice of vertical integration for fresh produce at the rural level.

The outcomes of this study have a key role in developing the rural regions and improving rural livelihoods via value addition. The awareness of commercial cultivation and value addition in rural areas needs to be improved. This will help farmers to earn better revenues with improved market prospects in comparison to the revenues obtained from the cultivation of staple/conventional crops.

In an era of cold chains and food processing, this study aims to disseminate awareness about value addition for commercial and fresh produces at the rural level. The implication of this study will improve rural produce marketability, rural employability and farmer profitability at the rural level with the level of vertical integration.

The purpose of the paper is to identify, analyze and select the enablers for vertical integration of Aloe vera supply chain (AVSC) so that rural employability will be enhanced in the context of Rajasthan, India.

Interpretive structural modeling (ISM) was proposed to develop a structural model to identify the right enablers for enhancing the rural employability and business prospects. Also, fuzzy-matrix cross-reference multiplication applied to classification (F-MICMAC) was applied to segregate the enablers into four clusters on the basis of their driving and dependence power. Finally, the significant enablers were selected.

Out of identified 13 enablers, three enablers (i.e. institute for training and research, transportation infrastructure and government incentives for value addition) were appearing at the bottom of the ISM structural model and also in the driving quadrant of driver-dependent diagram. Therefore, they are the significant enablers for vertical integration of AVSC to enhance the rural employability in the context of Rajasthan, India.

The interactions among enablers are not statistically validated. However, the empirical analysis and total interpretive structural modeling may be used for this purpose.

The outcomes of the study will provide the guidelines for implementation of vertical integration at the village level to enhance rural employability in the context of Rajasthan, India in specific.

Although a few studies have been reported in the literature related to value-addition process (vertical integration), but the modeling of enablers to segregate and identify the appropriate enablers for vertical integration of AVSC for enhancing employability at the rural areas is unique.

This paper aims to understand how organizations can apply the Blue Ocean Shift process to achieve profitable growth and make competition irrelevant.

This paper uses a case study approach. Based on interaction with the senior management of an organization and secondary sources, this paper presents an application of the Blue Ocean Shift process on a strategic move by an organization to achieve value innovation.

This paper presents a case of how Tata Motors Ltd. applied Blue Ocean Shift process to come up with the product Tata Ace, which achieved value innovation while making competition irrelevant. From assessing the current state of play to forming a motivated team, working with suppliers and fulfilling the needs of the non-customers and unhappy existing users, they were able to create a strong position for themselves.

Blue Ocean Strategy, through a process defined as Blue Ocean Shift, can be applied by organizations to achieve value innovation, change market boundaries and achieve profitable growth through their strategic offerings. It can help them get out of “red oceans” which may be a way to view the existing hypercompetitive world.

This paper contributes to the application of the Blue Ocean Shift process in the Indian context while studying a strategic move of an Indian firm. It showcases an example of how large Indian organizations can successfully apply the process to achieve value innovation.

The increase in automobile usage across the world has fortified the opportunities of maintenance service garages. However, there are significant numbers of challenges in front of maintenance service providers at all stages of the business. This paper identifies, analyzes and prioritizes various challenges associated with the establishment and survival of garages specific to Indian context.

In this paper, challenges for automotive service garage are identified through expert opinion, garage survey and literature. A structural hierarchical framework of the identified challenges is established through structural models, including interpretive structural modeling and analytic hierarchy process.

This paper has identified nine challenges, namely proliferation of new models and variants; technological advancements in automobile systems; demand of better service quality; space and ambience requirements; labor requirements; requirement of modern support equipments, tools and spares; safety requirements and prevention of occupational hazards; environmental norms and concerns; proper documentation requirements. The drivers and dependent variables have been identified. A hierarchical framework of challenges has been established.

This paper provides a comprehensive list of challenges and their priority in establishing an automobile maintenance garage business in Indian context. This will help the budding entrepreneurs and existing maintenance organizations to focus on the challenges that necessitate immediate attention and corrective actions.

This paper provides a significant contribution in the literature of garage maintenance services, which is established on the viewpoint of different collaborators associated with this business. This study will be a foundation to investigate further in this domain.

Over a two‐month period, the editor of this media review has searched worldwide for the most interesting and useful articles, blogs and books on the topic of strategic management.

In addition to his own finds, the editor sorted through suggestions by a team of veteran top managers and senior academics.

The result is a surprisingly diverse set of media articles about strategy and leadership on such topics as brand bruising, executive compensation at Detroit automakers, walled garden idea, Russian high‐tech boom, botnets threat, new LBO worker/management model, downsizing as restoration, four principles of luxury brands, growing economic ties between Asia and the Middle East, Indian automaker confront deregulation, addressing and adapting to global warming, commoditizing the Starbucks brand, Silicon Valley's geographical advantage, collaborative networks, new pricing strategies, dollar's reserve‐currency status.

URL links and references have been provided for the articles so that managers can easily follow up this quick scan of the media by reading the articles in full.

Provides a snapshot of what managers are reading and a guide to trends and fresh thinking.

Workflow optimisation is crucial for establishing a viable acute stroke (AS) intervention programme in a large tertiary care centre. This study aims to utilise Lean Six Sigma (LSS) principles to enhance the hospital's workflow.

The Action Research methodology was used to implement the project and develop the case study. The study took place in a large tertiary care academic hospital in India. The Define-Measure-Analyse-Improve-Control approach optimised the workflow within 6 months. Lean tools such as value stream mapping (VSM), waste audits and Gemba were utilised to identify issues involving various stakeholders in the workflow. Sigma-level calculations were used to compare baseline, improvement and sustainment status. Additionally, statistical techniques were effectively employed to draw meaningful inferences.

LSS tools and techniques can be effectively utilised in large tertiary care hospitals to optimise workflow through a structured approach. Sigma ratings of the processes showed substantial improvement, resulting in a five-fold increase in clinical outcomes. Specifically, there was a 43% improvement in outcome for patients who underwent acute stroke revascularisation. However, certain sigma ratings deteriorated during the control and extended control (sustainment) phases. This indicates that ensuring the sustainability of quality control interventions in healthcare is challenging and requires continuous auditing.

The article presents a single case study deployed in a hospital in India. Thus, the generalisation of outcomes has a significant limitation. Also, the study encounters the challenge of not having a parallel control group, which is a common limitation in quality improvement studies in healthcare. Many studies in healthcare quality improvement, including this one, are limited by minimal data on long-term follow-up and the sustainability of achieved results.

This study pioneers the integration of LSS methodologies in a large Indian tertiary care hospital, specifically targeting AS intervention. It represents the first LSS case study applied in the stroke department of any hospital in India. Whilst most case studies discuss only the positive aspects, this article fills a critical gap by unearthing the challenges of applying LSS in a complex healthcare setting, offering insights into sustainable quality improvement and operational efficiency. This case study contributes to the theoretical understanding of LSS in healthcare. It showcases its real-world impact on patient outcomes and process optimisation.

A novel cost-effective bio-digester was explored to convert biological waste into useful clean energy. The bioreactor was aimed to anaerobically digest locally sourced cow dung and chicken droppings.

The design consideration is a batch horizontal 267 L digester made from cast iron with centrally positioned four-impeller shaft to enhance mixing. The system operated with a retention time of 63 days and a substrate (cow dung and poultry waste) ratio of 1:2 and water substrate ratio of 1:0.5 in the gasholder system. The purification, compression and performance evaluation of the generated biogas were also conducted.

The total volume of gas produced for each substrate compositions designed over 14 days ranges between 49.34 and 52.91 mL/day. The optimal value of 52.45 ml using cow dung and poultry waste (w/w) 20:80 was obtained. The average ambient temperatures during the study were within the mesophilic range of 20-40°C. The pH values were stable and always in the optimal range of 6.5-8.0. The reductions in moisture content, ash content, total solids and volatile solids were from 80.50-0.20 per cent, 39.60-14 per cent, 18.50-5.90 per cent and 11.60-4.90 per cent, respectively.

The developed digester is cost-effective and would help minimize solid waste disposal. The estimated methane contents of the gas from cow dung and chicken waste after scrubbing were found to be 71.95 per cent and could be harnessed in solving the energy crisis in the developing nations.