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Milk cake is a well-renowned khoa-based dairy product in India, produced either from the buffalo milk or using a specific danedar variety of khoa. Under ambient conditions, shelf-life of milk cake is generally up to 3–4 days, whereas under refrigeration conditions, it can last up to 12–14 days. Therefore, the present study aims to evaluate the effect of modified atmosphere packaging (MAP) to enhance the shelf-life and keeping intact freshness of milk cake under refrigerated conditions (4 ± 2 °C).

Different gas concentrations of N₂ and CO₂ (70:30, 50:50 and 90:10) were used as a treatment, whereas control samples were kept under atmospheric air composition. The product was examined for sensory, physicochemical and microbiological parameters at weekly intervals.

The physicochemical and microbiological attributes displayed gradual elevation with progressive storage period in all the samples. However, the overall sensory profile of the product remained acceptable for a longer duration. Most of the quality parameters in control declined more rapidly with a shelf life of 14 days, in comparison to MAP packed samples, where gas flushing with the ratio 70:30 was found to be best suited for extending the shelf life of milk cake up to 28 days at refrigeration temperature.

To extend the shelf life of milk cake, modified atmosphere was provided with different gas ratios to reach a best-suited environment for sensory, storage life and proximate parameters.

Mergers and acquisitions (M&A) are common strategies of firms to increase its performance. Although the motives of M&A are different, the determinants are discreet. The purpose of this paper is to determine the factors affecting M&A activities in the Indian pharmaceutical sector.

Using a balanced panel data of the pharmaceuticals sector in India, this study arrives at the determinants of M&A. The authors use regression techniques such as panel probit models, ordered probit models and matching techniques for a comparable and robust estimates for the factors related to M&A activities at firm level.

The empirical findings suggest that export intensity, import intensity, firm size and R&D intensity as the major determinants of M&A in the Indian pharmaceutical sector. In the context of acquisition, there is a riskiness associated with the any business strategy, for to which a firm may choose to finance the deal either via cash, stock or assets. This study further looks at the firm’s decision on the types of acquisitions and arrives at the determinants of such decisions. The factors such as capital intensity were found more important when acquisition by share was undertaken compared to others. The success of the M&A is observed by considering the financial performance of the firm measured in terms of the profit margin at firm level. Using the propensity score matching technique, this study concludes that M&A have a positive effect on the profit margin in the post-M&A scenario.

The study seeks to add to the existing literature and empirical work done in the field of M&A, by not only looking at determinants that motivate a firm to merge and/or acquire but also if the decision of the firm is reflected positively in the firm’s performance. The study concludes that export intensity is an important factor for the pharmaceutical firms in India since exports are a major proportion of firm’s total sales. Technology transfers as technology imports and R&D conducted by the firm are both very important for the drug manufacturers. Any gap in the flow of drugs to the market would hamper the growth of the firm. The growth of the pharmaceutical industry depends on the close collaboration between small R&D units that lack resources to sell their work and large business houses, both domestic and foreign affiliated that will provide them the required market. However, all comprehensive work has been done in this study to cover all aspects of M&A including the financial pathway taken by the firm yet, the study has certain limitations as it does not take into account the entry and exit of firms from the industry.

Policies related to small and large firms should aim at making them export oriented and multinational affiliated to compete at the international market with corporate restructuring through M&A. This will help in firm’s growth and sharing of knowledge capital.

No such study is conducted that differentiate type of M&A and their determinants for the Indian pharma sector.

In the recent post-pandemic era, the globe has been anxious for the sustainable disposal of healthcare waste to protect public health, protect the environment and enhance future preparedness. Developing countries, in particular, have struggled to dispose of healthcare waste (HCW) to eradicate the hazardous effects of medical waste generated during and after the deadly COVID-19 pandemic. Hence the purpose of the research paper is to develop a hybrid decision-making framework to identify various barriers for sustainable disposal of healthcare waste use of Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) and Analytical Network Process (ANP).

A hybrid framework of Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) and Analytical Network Process (ANP) has been used to rank barriers and sub-barriers in the disposal of healthcare waste.

The study’s findings suggest that lack of segregation practices, absence of green procurement policy, obsolete technologies and resistance to adopting change management are the topmost causal barriers influencing the remaining barriers. Lack of commitment among healthcare administrations, lack of standard performance measures and resistance to adopting change appear to be the topmost crucial barriers.

The study’s finding enables all stakeholders to prioritize the barriers systematically for better performance and save resources during the process. The policymakers can use the results to design a clear regulatory framework.

The literature has highlighted the factors and their association with the disposal of healthcare waste mainly in isolation. The results are validated against the Grey-Analytical Hierarchy Process (G-AHP) to ensure the robustness of the proposed framework. This paper is one of the preliminary attempts to propose a framework of the interrelationships of the factors that have a direct role in survival for management education.

This study aims to bring awareness to the developing of fault detection systems using the data collected from sensor devices/physical devices of various systems for predictive maintenance. Opportunities and challenges in developing anomaly detection algorithms for predictive maintenance and unexplored areas in this context are also discussed.

For conducting a systematic review on the state-of-the-art algorithms in fault detection for predictive maintenance, review papers from the years 2017–2021 available in the Scopus database were selected. A total of 93 papers were chosen. They are classified under electrical and electronics, civil and constructions, automobile, production and mechanical. In addition to this, the paper provides a detailed discussion of various fault-detection algorithms that can be categorised under supervised, semi-supervised, unsupervised learning and traditional statistical method along with an analysis of various forms of anomalies prevalent across different sectors of industry.

Based on the literature reviewed, seven propositions with a focus on the following areas are presented: need for a uniform framework while scaling the number of sensors; the need for identification of erroneous parameters; why there is a need for new algorithms based on unsupervised and semi-supervised learning; the importance of ensemble learning and data fusion algorithms; the necessity of automatic fault diagnostic systems; concerns about multiple fault detection; and cost-effective fault detection. These propositions shed light on the unsolved issues of predictive maintenance using fault detection algorithms. A novel architecture based on the methodologies and propositions gives more clarity for the reader to further explore in this area.

Papers for this study were selected from the Scopus database for predictive maintenance in the field of fault detection. Review papers published in this area deal only with methods used to detect anomalies, whereas this paper attempts to establish a link between different industrial domains and the methods used in each industry that uses fault detection for predictive maintenance.

The purpose of this technical paper is to explore the application of analytics and Six Sigma in the manufacturing processes for iron foundries. This study aims to establish a causal relationship between chemical composition and the quality of the iron casting to achieve the global benchmark quality level.

The case study-based exploratory research design is used in this study. The problem discovery is done through the literature survey and Delphi method-based expert opinions. The prediction model is built and deployed in 11 cases to validate the research hypothesis. The analytics helps in achieving the statistically significant business goals. The design includes Six Sigma DMAIC (Define – Measure – Analyze – Improve and Control) approach, benchmarking, historical data analysis, literature survey and experiments for the data collection. The data analysis is done through stratification and process capability analysis. The logistic regression-based analytics helps in prediction model building and simulations.

The application of prediction model helped in quick root cause analysis and reduction of rejection by over 99 per cent saving over INR6.6m per year. This has also enhanced the reliability of the production line and supply chain with on-time delivery of 99.78 per cent, which earlier was 80 per cent. The analytics with Six Sigma DMAIC approach can quickly and easily be applied in manufacturing domain as well.

The limitation of the present analytics model is that it provides the point estimates. The model can further be enhanced incorporating range estimates through Monte Carlo simulation.

The increasing use of prediction model in the near future is likely to enhance predictability and efficiencies of the various manufacturing process with sensors and Internet of Things.

The researchers have used design of experiments, artificial neural network and the technical simulations to optimise either chemical composition or mould properties or melt shop parameters. However, this work is based on comprehensive historical data-based analytics. It considers multiple human and temporal factors, sand and mould properties and melt shop parameters along with their relative weight, which is unique. The prediction model is useful to the practitioners for parameter simulation and quality enhancements. The researchers can use similar analytics models with structured Six Sigma DMAIC approach in other manufacturing processes for the simulation and optimisations.

The purpose of this study is to investigate the impact of business group (BG) affiliation on affiliated firms' entrepreneurial orientation (EO). The authors further investigate the possible contingent factors affecting this relationship – the age of BGs and the affiliated firm’s external linkages (ratio of external to in-house interlocks) on the relationship in an emerging market context.

The study employs a dynamic panel data framework using the system-generalized method of moments (Sys-GMM) on a sample of 670 NSE-listed Indian firms during the 2006–2019 period. EO is measured through content analysis of the letters to shareholders (LTS) issued by the companies between the period 2006 and 2019.

BG affiliates have more EO than standalone firms, as affiliates can access group-wide resources and capabilities apart from firm-specific resources. Affiliates of older BG have less EO since they are more entrenched in the institutional settings of their BG. Affiliates with more external linkages of board members will have a higher level of EO, as such linkages would subside inertial tendencies by exposing them to novel sets of information, resources and strategic practices. Further, the negative effect of BG age on EO is countered by external linkages. Overall, the study shows that the effect of group affiliation is not uniform and is contingent on the factors we have theorized and tested.

The paper proposes the resource-based view and the institutional void theory as likely candidates for explaining the contribution of BGs towards the EO of its affiliates, especially in the context of emerging markets. The contingent role of BG age highlighted in the paper forewarns managers about the importance of establishing internal mechanisms to preserve the EO in affiliates. Our findings about the positive role played by external linkages of the board members provide one such mechanism that can be leveraged to enhance affiliated firm’s EO.

The purpose of this paper is to holistically study barriers in the path of implementation of retirement planning, as the need is increasing with decrease in mortality. The proper retirement planning can be one of the most important tools to control financial expenses on healthcare and welfare on old age population in government budgets.

The paper is a blend of theoretical framework and practical application and uses interpretive structural modeling (ISM) analysis to draw linkage and impact of identified barriers in the path of achievement of goals of retirement planning. The study has used three different research phases: identification of barriers from the literature, interviews with experts of industry at second stage and designing an ISM impact matrix cross-reference multiplication model. The identification phase led to the selection of 15 factors from past literature and by suggestion from industrial experts.

This study seeks to identify which barrier is acting as the most dominant one for the mass adoption of retirement planning and this result is helpful for policymakers to remove the dominant barrier. The result of this analysis can make retirement planning easy by elimination of highlighted barriers on the basis of their importance in the path of achievement of retirement goals. In the ISM level diagram, barriers such as marital status, number of financial dependents at the bottom, gender, income level, educational level, financial literacy, financial dependency, policy regulation, terms and conditions, goal clarity and psychological and cultural factors are on the top. Barrier of macroeconomic and bureaucratic impediments are also very important factors for achievement of retirement goal of an individual, but they cannot be controlled directly by the associated members of industry.

The concern for providing sufficient retirement resources is growing with the increase in life expectancy for human beings. Such requirement has attracted views from not only academicians but also policymakers. This paper is one of the preliminary attempts to identify barriers in implementation of retirement planning and rank them according to their importance.

This paper proposes a decision-making framework for assessing various dimensions and barriers that have affected the admission process in management educational institutions during the ongoing pandemic. The framework considers the interrelationship between the obstacles and highlights the importance of each barrier.

An integrated method based on decision-making trial and evaluation laboratory and analytical network process is proposed to structure the barrier assessment framework. Results obtained from the study are validated by comparing them against the conventional analytical hierarchy process.

The results obtained from this study indicate four significant dimensions that hinder admission in Indian management institutes, namely, governmental, financial, sectoral, institutional and market. The top five barriers are demand shift towards technical (alternative) skills, acceptance of the graduated students, lack of industry–institute collaboration, lack of long-term vision and opening new Indian Institute of Technologies (IITs) and Indian Institute of Managements (IIMs).

During this ongoing pandemic, many educational institutes have been forced to shift from the traditional classroom to a virtual teaching model. In this regard, this study helps identify and assess the barriers to admission in Indian management institutes during this epidemic and thus, contribute to the literature. The findings will assist all stakeholders and policymakers of management institutions design and develop appropriate managerial strategies. The study is conducted in the Indian management educational institute context and can be extended to technical education institutions for deeper insights.

The paper develops an assessment framework for analysing the barriers to admission in Indian management institutes during the ongoing COVID-19 pandemic. Research implications are discussed in the context of a developing country.

This study aims to formulate a conceptual sustainable framework for developing a trusted, reliable, scalable, transparent, traceable and sustainable agri-food supply chain in a developing country so that it minimizes wastage and increases the efficiency levels of agri-produce and its usage.

This study uses a rigorous review of extant literature, case studies and the interview method for theory building, using blockchain technology (BT) as a subject. Further, the study builds a framework to relate blockchain solutions to the challenges faced by the agri-supply chain. Notably, the use of BT in the agri-food supply chain is a relatively new area of study.

Limitations of using BT 3.0 in a diverse supply chain like the food sector, especially in a developing country such as India, may be overcome by adopting BT 4.0 and could change the country’s face by controlling inefficiencies and ensuring transparency, helping in good governance, improving the humanitarian supply chain and integrating the bottom of the pyramid to the main economy. Based on the findings, this study proposes BT 4.0 for the agri-supply chain in India to deal with the current issues of demand-supply gap, wastages of agri-produce, unequal distribution of profit among agriproduct producers and logistics suppliers and ensuring sustainability.

Results in this study have been derived from a specific demographic condition in India. Future research with other demographic conditions may be replicated. BT is a new technology product, and its effectiveness is yet to be established.

The outcome of this study provides the application of BT 4.0 in the area of the agri-food supply chain. The BT 4.0 framework has been developed on studying a few cases that either implemented BT or were in the testing phase. The benefits of the agri-food supply chain vis-à-vis its overall social well-being may be achieved on the successful implementation of the framework, despite existing complexities in the food supply chain. Further research on this subject may help the other dimensions of the complexity of adopting BT 4.0. Both practitioners and policymakers from developing countries can, therefore, use the findings of this study to analyze BT 4.0 and address the concerns of the agri-food supply chain.

This research paper has proposed a conceptual framework of BT 4.0, which is a completely new technology. It is fairly transparent, and therefore sustainable supply chain practices may be achieved easily.

Improving work engagement can have significant implications for performance at individual, team and organisational level. The purpose of this paper is to investigate the effects of occupational self efficacy and human resource development (HRD) climate on work engagement among business executives of select business organisations in India. In addition, it aims to attempt to examine the mediating effect of HRD climate on self efficacy and work engagement relationship.

The sample consisted of 150 business executives from both public and private sector manufacturing and service organisations in India. Data were collected through both personal visits and online questionnaires. Correlation and regression analyses were used to test the research hypotheses. Specifically, Baron and Kenny's method was used for testing the hypotheses of mediation.

A significant relationship was found between all variables in the study. All the study hypotheses were supported. HRD climate was found to partially mediate the relationship between occupational self‐efficacy and work engagement. Interestingly, both HRD climate and self‐efficacy affect work engagement both directly and indirectly through influencing the other.

Work engagement requires the workforce that is endorsed with self‐efficacy as dispositional trait. In addition, improving the HRD climate can have significant implications for enhancing the work engagement among Indian business executives.

By investigating the relationship between self‐efficacy, HRD climate and work engagement the present study made an effort to fulfil the gap in academic literature where there is a significant dearth of academic literature on work engagement from developing economies.