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The global outbreak of COVID-19 and its subsequent varied impacts on different economic activities necessitate to examine its disruptions and impacts on livestock sector in India due to its recently surging potential as an unrivaled alternative to boost farmer’s income.

The studies for review were identified through search in different databases using relevant keywords. Only full text papers written in English language were reviewed. The review was organized and streamlined using Covidence software.

Analysis of the literature reveals adverse effects of COVID-19 on functioning of input and output stages of livestock supply chains. This has resulted in upstream and downstream economic losses that affect livelihoods of the producers.

Scale of unprecedented crisis due to COVID-19 pandemic requires creative policy decisions to make livestock production systems robust, resilient and sustainable. Organized production systems are required to integrate with livestock-tech startups to modernize their supply chains, whereas local supply chains are required to reorient with government’s intervention in terms of developing on-farm production and postproduction processing facilities.

Although there exist some evidence on COVID-19-related impacts on livestock sector of India, but an integrated review of evidence on COVID-19 related disruptions at all the stages (from input supply to marketing) of livestock supply chains was missing.

The global research evidences indicate that the technology adoption in case of agribusiness has a potential to enhance the performance and bring operational efficiency. India is the world’s largest producer as well as consumer of milk but struggles with yield per cattle, overall productivity, low rate of technology acceptance and adoption, health detection of milching units, animal data recording and presence of dairy products in the global market. The purpose of this study is to focus on identifying the challenges of technology adoption in dairy farms and constructing a hierarchical model using soft systems methodology.

This study uses nominal group technique-based discussion with domain experts and personal interviews with dairy farm owners/managers for the identification of challenges, fuzzy interpretative structural modeling as well as FMICMAC to develop a hierarchical model of challenging elements and to divide the identified elements into four categories based on the dominance of driving-dependence power.

This research has developed a list of 12 challenges affecting the technology adoption in a dairy farm business unit, identified through the personal interviews with 60 dairy farms across three highest milk-producing states of India in terms of annual milk output – Haryana, Punjab and Uttar Pradesh. Lack of government support followed by lack of educational opportunities in dairy-based education were found as the most crucial and high driving challenges, whereas high cost, huge investment and low acceptance of decision-maker were found as the most dependent challenges of technology adoption.

This research is one step ahead of interpretive structural modeling that considers the fuzzy-based dominance in the model to showcase the degree of relationship along with its existence, but it lacks to statistically validate the findings using techniques like SEM.

This paper has developed a list of challenges in adoption of technology along with their inter-relationships to highlight the required focus challenge that drives or is dependent on the other challenges. The goal is to bring performance improvement and assist Indian dairy farm business stakeholders or decision-makers in formulating strategic and action plans and help policy planners to make favorable policies based on the understanding of contextual relationship between challenges.

In Indian context, dairy is an important part of agriculture sector, and milk is an essential item that facilitates income generation to small and rural households and a source item for several other businesses and activities. The results of this research suggested the policy planners and government to ensure subsidized and insured technologies, training support and facilities, educational opportunities and efforts for promotion of technology adoption among dairy farmers. The suggestions are purely on the basis of the relevance of challenges in the hierarchy and can play a significant role in improving the level of technology adoption and can ultimately uplift the social and economic well-being from micro-level of farmers to macro-stage concerning economic development of India.

To the best of the authors’ knowledge, this study is purely original and outcome of the research conducted by authors.

This article tackles the intersection of mothering and labor through the author's own experience as a feminist mother/manager from Istanbul, Turkey. It aims to revisit the first years of motherhood, exploring the struggle to invent a peculiar maternal subjectivity in opposition and negotiation with the patriarchal institution of motherhood, the new definition of maternal labor in a highly digital, neoliberal context and the issue of marital fairness in a dual-income heterosexual marriage.

The article presents an autoethnographic, retrospective and introspective inquiry into the first seven years of the author's mothering experience in order to offer an in-depth exploration of the various aspects of contemporary maternal labor.

The article shows how maternal labor has shifted in nature and expanded in scope in a contemporary non-Western context. It investigates the dissolution of the spatial, temporal and sensorial boundaries between the managerial labor dedicated to the workplace, and to the family. Highlighting the similarities of the two forms of labor, the article manifests the materiality, tangibility and visibility of maternal labor.

Further intersectional studies shall be beneficial to redefine maternal labor in different contexts.

Departing and diverting from the terms “invisible labor” and “mental load”, the article suggests a shift in terminology to stress the multifaceted medley of managerial tasks mothers undertake today.

The article provides an original take on maternal labor through the first-hand experience of a middle-class, professional mother from Istanbul, Turkey.

The purpose of this paper is to introduce a three-echelon multimodal transportation problem applied to a humanitarian logistic case study that occurred in Mexico.

This study develops a methodology combining a transshipment problem and an adaptation of the multidepot heterogeneous fleet vehicle routing problem to construct a mathematical model that incorporates the use of land-based vehicles and drones. The model was applied to the case study of the Earthquake on September 19, 2017, in Mexico, using the Gurobi optimization solver.

The results ratified the relevance of the study, showing an inverse relationship between transportation costs and delivery time; on the flip side, the model performed in a shorter CPU time with medium and small instances than with large instances.

While the size of the instances limits the use of the model for big-scale problems, this approach manages to provide a good representation of a transportation network during a natural disaster using drones in the last-mile deliveries.

The present study contributes to a model that combines a vehicle routing problem with transshipment, multiple depots and a heterogeneous fleet including land-based vehicles and drones. There are multiple models present in the literature for these types of problems that incorporate the use of these transportation modes; however, to the best of the authors’ knowledge, there are still no proposals similar to this study.

Despite large bodies of research related to the impacts of e-commerce on last-mile logistics and sustainability, there has been limited effort to evaluate urban freight using an equity lens. Therefore, this study proposes a modeling framework that enables researchers and planners to estimate the baseline equity performance of a major e-commerce platform and evaluate equity impacts of possible urban freight management strategies. The study also analyzes the sensitivity of various operational decisions to mitigate bias in the analysis.

The model adapts empirical methodologies from activity-based modeling, transport equity evaluation, and residential freight trip generation (RFTG) to estimate person- and household-level delivery demand and cargo van traffic exposure in 41 U.S. Metropolitan Statistical Areas (MSAs).

Evaluating 12 measurements across varying population segments and spatial units, the study finds robust evidence for racial and socio-economic inequities in last-mile delivery for low-income and, especially, populations of color (POC). By the most conservative measurement, POC are exposed to roughly 35% more cargo van traffic than white populations on average, despite ordering less than half as many packages. The study explores the model’s utility by evaluating a simple scenario that finds marginal equity gains for urban freight management strategies that prioritize line-haul efficiency improvements over those improving intra-neighborhood circulations.

Presents a first effort in building a modeling framework for more equitable decision-making in last-mile delivery operations and broader city planning.

The purpose of this paper is to investigate the research landscape of LSS 4.0 papers published in two well-known repositories, Scopus and Web of Science (WoS), in terms of publication trends, article distribution by author, journal, affiliations and country, and article clustering based on keywords, authors and countries. In addition, a literature review was carried out to build a conceptual framework of integrated Lean Six Sigma and Industry 4.0 (LSS 4.0) that encompasses operational, sustainability and human factors or ergonomics aspects.

The literature review of integrated Lean Six Sigma and I4.0 publications published in Scopus and WoS databases in the current decade was conducted for the present study. This study categorizes LSS, I4.0 and related research articles based on publication patterns, journals, authors and affiliations, country and continental-wise distribution and clustering the articles based on keywords and authors from the Scopus and WoS databases from 2011 to 2022 using the search strings “Lean”, “Six Sigma”, “Lean Six Sigma” and “Industry 4.0” in the Title, Abstract and Keywords using Biblioshiny, VOS viewer and Microsoft Excel.

In the recent three years, from 2020 to 2022, LSS 4.0 has been substantially increasing and is seen as an emerging and trending area. This research identifies the most influential authors, most relevant affiliations, most prolific countries and most productive journals and clusters based on keywords, authors and countries. Further, a conceptual framework was developed that includes the impact of operational, sustainability and ergonomic or human factors in LSS 4.0.

This article assists in comprehending the trends and patterns of LSS 4.0. Further, the conceptual framework helps professionals and researchers understand the significance and impact of integrating LSS and Industry 4.0 in the aspects of human factors/ergonomic, sustainability and operations. Also, the research induce professionals to incorporate all these factors while designing and implementing LSS 4.0 in their organization.

This conceptual framework and bibliometric analysis would aid in identifying potential areas of research and providing future directions in the domain of LSS 4.0. It will be beneficial for academicians, professionals and researchers who are planning to apply and integrate techniques of LSS and technologies of I4.0 in their organizations and research.

The purpose of this paper is to gain insight into how management accountants can become relevant business partners out of respect for existing locally developed accounts of economic performance for decision-making.

The paper is based on qualitative semi-structured interviews with local business actors, in this case, families from seven financially successful Danish dairy farms. The casework and the analysis have been informed by pragmatic constructivism.

The local business actors do not use the official accounting system for ongoing cost-management-related decision-making. Instead, they use several epistemic methods that include locally developed decision models, experiences, rules of thumb and intuition. The farmers use these vernacular accountings to compensate for the cost management illusion that the formal accounting system tends to create. What the study suggests is that when management accountants engage as business partners, they are likely to enter a space where accounting is already present.

This paper argues that local business actors practice epistemic methods where they develop and use vernacular accountings to support their managerial practice, also in the absence of a professional management accountant. These vernacular accountings may lead the local actors into an illusion because the vernacular accountings do not necessarily have an inherent economic logic and theoretical reliability. The role of the management accountant in such a setting is hence to understand, support and advance local epistemic methods. Becoming a business partner requires a combination of management accounting analytical skills and a sense of empathy and sensitivity regarding what is already at play and how this can become an object of discussion without violating the values of the other.

This study aims to examine the impact of Lean 4.0 practices on value co-creation in the dairy ecosystem.

Data collection were carried out through a questionary application with 126 professionals linked to the dairy ecosystem, including milk producers, milk cooperatives and milk transporters. The data were analyzed using Cluster Analysis, Mann-Whitney test and Chi-Square test.

A strong relation was found between the use of Lean 4.0 tools and the increase in operational performance, in addition to milk quality. Moreover, it can be noted that the use of digital technologies from Industry 4.0 has a strong relation with dairy production optimization, in other words, it is possible to be more efficient in the dairy process via Lean 4.0 adoption.

The study is limited to analyzing the Brazilian dairy ecosystem. The results presented may not reflect the characteristics of the other countries.

Once the potential empirical impacts of the relation between Lean 4.0 and value co-creation are elucidated, it is possible to direct strategies for decision-making and guide efforts by researchers and professionals to deal with the waste mitigation present in the dairy sector.

Lean 4.0 proves to be a potential solution to improve the operational performance of the dairy production system. Lean 4.0, linked to value co-creation, allows the integration of the production sector with consumers, through smart technologies, so new services and experiences can be provided to the consumer market. Additionally, the consumer experience can be stimulated based on Lean 4.0, once the quality specification is highlighted based on data science and smart management control.

To the best of the authors’ knowledge, this is the first study that analyzes the interrelationship between the Lean 4.0 philosophy and the value co-creation in the dairy ecosystem. In this sense, the study reveals the main contributions of this interrelation to the dairy sector via value co-creation, which demonstrates a new perspective on the complementarity of resources, elimination of process losses and new experiences for the user through digital technologies integrated with the Lean Thinking approach.

With the current wave of modernization in the dairy industry, the global dairy market has seen significant shifts. Making the most of inventory planning, machine learning (ML) maximizes the movement of commodities from one site to another. By facilitating waste reduction and quality improvement across numerous components, it reduces operational expenses. The focus of this study was to analyze existing dairy supply chain (DSC) optimization strategies and to look for ways in which DSC could be further improved. This study tends to enhance the operational excellence and continuous improvements of optimization strategies for DSC management

Preferred reporting items for systematic reviews and meta-analyses (PRISMA) standards for systematic reviews are served as inspiration for the study's methodology. The accepted protocol for reporting evidence in systematic reviews and meta-analyses is PRISMA. Health sciences associations and publications support the standards. For this study, the authors relied on descriptive statistics.

As a result of this modernization initiative, dairy sector has been able to boost operational efficiency by using cutting-edge optimization strategies. Historically, DSC researchers have relied on mathematical modeling tools, but recently authors have started using artificial intelligence (AI) and ML-based approaches. While mathematical modeling-based methods are still most often used, AI/ML-based methods are quickly becoming the preferred method. During the transit phase, cloud computing, shared databases and software actually transmit data to distributors, logistics companies and retailers. The company has developed comprehensive deployment, distribution and storage space selection methods as well as a supply chain road map.

Many sorts of environmental degradation, including large emissions of greenhouse gases that fuel climate change, are caused by the dairy industry. The industry not only harms the environment, but it also causes a great deal of animal suffering. Smaller farms struggle to make milk at the low prices that large farms, which are frequently supported by subsidies and other financial incentives, set.

This paper addresses a need in the dairy business by giving a primer on optimization methods and outlining how farmers and distributors may increase the efficiency of dairy processing facilities. The majority of the studies just briefly mentioned supply chain optimization.

This research attempted to establish the underlying dimensions of supply chain management practices, blockchain technology and supply chain performance in the Indian dairy industry. Additionally, the study proposes a conceptual model that shows the mediating effects of blockchain technology in the relationship between supply chain management practices and supply chain performance.

Structural equation modelling (SEM) is incorporated to examine the proposed model using SPSS and AMOS version 24. The study population includes 119 registered Indian dairy processing units operating in Uttar Pradesh and New Delhi (source: Dairy – India). Individual registered dairy processing unit's top four executives, that is Head of the Dairy Processing Plant, Supply Chain head and Marketing Head, and IT head are chosen as the respondents of the study, which renders the sample size of 476. Judgmental sampling based on the organisation's market position and plant production capacity (i.e. one lakh litre per day) has been set as the benchmark for selecting the dairy processing units. The executives are selected as respondents as they are well-versed in the phenomenon of supply chain management practices, blockchain technology and supply chain performance compared to other staff working in the dairy industry. The data was collected from December 2021 to March 2022 through judgmental sampling. The target sample size was 476, but only 286 questionnaires were received in a completed state and were further used for analysis.

Manufacturing practices, information sharing, distribution management, inventory management and blockchain technology have a significant and positive impact on supply chain performance in the Indian dairy industry. Furthermore, the research demonstrates that blockchain technology partially mediates the relationship between supply chain management practices and supply chain performance in the context of the Indian dairy industry.

This research is focused on the Indian dairy industry operating in only two states, namely New Delhi and Uttar Pradesh. More research is needed to determine whether SCM practices and the prospects for blockchain technology among channel members are universally applicable to merchants in non-dairy products. Similar investigations should be carried out on dairy industry operating in various formats and in numerous geographic locations. Further, case studies can be conducted by future researchers to learn how supply chain management methods are deployed, what precisely these practices entail and what costs and time demands are required by these practices in context of small independent retailers across different germane expanse.

While the available literature on the research area is spread out, the influence of blockchain technology in the Indian dairy industry has not yet been sufficiently analysed. Therefore, the research article focused on exploring underlying dimensions of the constructs of supply chain management practices, blockchain technology adoption and supply chain performance in the context of the Indian dairy industry.