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Cloud users can access services at anytime from anywhere in the world. On average, Google now processes more than 40,000 searches every second, which is approximately 3.5 billion searches per day. The diverse and vast amounts of data are generated with the development of next-generation information technologies such as cryptocurrency, internet of things and big data. To execute such applications, it is needed to design an efficient scheduling algorithm that considers the quality of service parameters like utilization, makespan and response time. Therefore, this paper aims to propose a novel Efficient Static Task Allocation (ESTA) algorithm, which optimizes average utilization.

Cloud computing provides resources such as virtual machine, network, storage, etc. over the internet. Cloud computing follows the pay-per-use billing model. To achieve efficient task allocation, scheduling algorithm problems should be interacted and tackled through efficient task distribution on the resources. The methodology of ESTA algorithm is based on minimum completion time approach. ESTA intelligently maps the batch of independent tasks (cloudlets) on heterogeneous virtual machines and optimizes their utilization in infrastructure as a service cloud computing.

To evaluate the performance of ESTA, the simulation study is compared with Min-Min, load balancing strategy with migration cost, Longest job in the fastest resource-shortest job in the fastest resource, sufferage, minimum completion time (MCT), minimum execution time and opportunistic load balancing on account of makespan, utilization and response time.

The simulation result reveals that the ESTA algorithm consistently superior performs under varying of batch independent of cloudlets and the number of virtual machines’ test conditions.

This study aims to identify the critical factors (barriers and drivers) influencing the adoption of cloud computing (ACC) in the manufacturing sector in India.

In this study, a mixed methodology approach is used. Interviews are conducted to investigate factors (drivers and barriers) influencing the ACC, which are further categorized as controllable determinants (weaknesses and strengths) and uncontrollable determinants (threats and opportunities) using a SWOT analysis. Fuzzy analytic hierarchy process (FAHP) has been utilized to highlight the most critical drivers as well as barriers. Finally, decision-making trial and evaluation laboratory (DEMATEL) has been used to find the cause-effect relationships among factors and their influence on the decision of adoption.

The manufacturing sector is in the digital and value change transformation phase with Industry 4.0, that is, the next industrial revolution. The 24 critical factors influencing ACC are subdivided into strengths, weaknesses, opportunities and threats. The FAHP analysis ranked time to market, competitive advantage, business agility, data confidentiality and lack of government policy standards as the most critical factors. The cause-effect relationships highlight that time to market is the most significant causal factor, and resistance to technology is the least significant effect factor. The results of the study elucidate that the strengths of ACC are appreciably more than its weaknesses.

This study couples the technology acceptance model (TAM) with technology-organization-environment (TOE) framework and adds an economic perspective to examine the significant influences of ACC in the Indian manufacturing sector. Further, it contributes to the knowledge of ACC in general and provides valuable insights into interrelationships among factors influencing the decision and strategies of adoption in particular.

This is the first scholarly work in the Indian manufacturing sector that uses the analysis from SWOT and FAHP approach as a base for identifying cause-effect relationships between the critical factors influencing ACC. Further, based on the extant literature and analysis of this work, an adoption framework has been proposed that justifies that ACC is not just a technological challenge but is also an environmental, economic and organizational challenge that includes organizational issues, costs and need for adequate government policies.

The study examined a wide range of proactive supply chain practices to demonstrate a cross-linkage among them and to understand their effects on both practitioners of previous decision-making models, frameworks, strategies and policies. Here, six supply chain practices are empirically evaluated based on 28 constructs to investigate a comprehensive model and confirm the connections for achieving performance and competence. The study presents a conceptual model and examines the influence of many crucial factors, i.e. supply chain collaboration, knowledge, information sharing, green human resources (GHR) management and lean-green (LG) practices on supply chain performance.

Structural equation modeling (SEM) examines the conceptual model and allied relationship. A sample of 175 respondents' data was collected to test the hypothesized relations. A resource based view (RBV) was adopted, and the questionnaires-based survey was conducted on the Indian supply chain professionals to explore the effect of LG and green human resource management (GHRM) practices on supply chain performance.

The study presented five constructs for supply chain capabilities (SCCA), five constructs for supply chain collaboration and integration (SCIN), four constructs for supply chain knowledge and information sharing (SCKI), five constructs for GHR, five constructs for LG practices (LGPR) and four constructs for lean-green SCM (LG-SCM) firm performance to be utilized for validation by the specific industry, company size and operational boundaries for attaining sustainability. The outcome emphasizes that SCCA positively influence GHRM, LG practices and LG supply chain firm performance. However, LG practices do not influence LG-SCM firm performance, particularly in India.

The study exploited multiple practices in a conceptual model to provide a widespread understanding of decision-making to assist in developing a holistic approach based on different practices for attaining organizational sustainability. The study stimulates the cross-pollination of ideas between many supply chain practices to better understand SCCA, SCIN, SCKI, GHRM and LG-SCM under a single roof for retaining organization performance.

This paper aims to examine the dynamism of causal relationships among cloud computing (CC) adoption factors in the Indian context, considering the perspectives of both the cloud adopter and cloud provider.

The case-study method has been used to understand the dynamics among the factors. Using data from specific cases in India, causal loop diagrams (CLDs) have been developed. System dynamic modeling (SDM) and simulation are used to study the relationships and their effect on the adoption rate.

The results revealed that adoption of CC depends on various factors such as persuasion (time-saving, cost-saving and word of mouth) and constraint factors (security and financial loss). However, it is seen that the adoption rate is very sensitive to changes in adoption per contact and word of mouth. Further, the adopter firm has a quicker time to market, which gives an added advantage to the firm. Also, with CC services, a firm can fulfill its projects or clients' requirements with little to no upfront investment in information technology (IT) services.

Lack of security, standardization and undefined service-level agreements are a few pressing issues that make it difficult for firms to evaluate the performance and reliability of services. Hence, immediate attention is needed to make transparent policies on CC and its services, thereby building trust.

This is the first and only work that has tried to explore and empirically test the dynamics of critical factors while making an adoption decision, considering both the adopter and provider perspectives. This study shows the journey of a firm, starting from being a prospective adopter to an adopter and continuous user. The work also empirically tested how adopters of technology benefit from the technology.

This study investigates the impact of supplier visibility on the adoption of sustainable practices and supply chain performance. The paper applies contingent Resource-Based View to explain how information sharing with customers and suppliers and supply chain traceability has influenced visibility; visibility has impacted supply chain velocity sustainable practices, and finally, supply chain performance.

This research analyses 263 survey responses from UK retail (grocery) stores' executives and managers for perishable food during the COVID-19 pandemic.

The research results indicate that both supply chain traceability and information sharing (customers) positively influence visibility. Further, visibility positively influences the adoption of sustainable practices and velocity, positively impacting supply chain performance. However, information sharing with the customer has no significant influence on performance, and information sharing with the supplier has no significant relationship with visibility.

This research is the first attempt that explores the contingent Resource-Based View for the perishable food supply chain. Further, the empirical evidence provides meaningful insights for academics and industry by filling a crucial lacuna in the literature.

The purpose of this paper is to presents an analysis of geographically and disciplinary scattered academic publications of cloud computing (CC) research in information systems. This review aims to understand the research methodology, research frameworks and models, geographical distribution, trends, critical factors and causal relationships associated with cloud computing adoption (CCA).

Systematic-literature-review using natural language processing is conducted to explore the phenomenon. The relevant research studies are extracted from various online databases using quality-assessment-criteria.

The study is a novel attempt to highlight the differences in critical factors for CCA in different country-settings. Further, the research explores the causal relationships among the identified factors. The findings of this 12-year systematic-review contribute by aiding the providers and potential adopters to devise context-specific strategies for the penetration of cloud services and sound adoption decisions (ADs), respectively. The findings also highlight the prospective avenues of research in the domain for researchers. Using the in-depth analysis, conceptual frameworks have been proposed that can assist in exploring the pre-adoption and post-adoption of CC.

This study contributes to CCA research by providing holistic insights into the methodology, research framework and models, geographical focus, critical factors and causal relationships influencing the AD or intention. The review highlights the unexplored emerging research topics in the field of CCA for future research directions.

Today, proficient practices are required to stimulate along various boundaries of the supply chain (SC) to exploit manufacturing resources economically, effectually and gracefully for retaining operational excellence. Accordingly, varieties of paramount practices, i.e. Lean, Agile, Resilient and Green practices, are integrated in present study with the objective to develop a Decision Support Framework (DSF) to select robust supplier under the extent of Lean-Agile-Resilient-Green (LARG) practices for a manufacturing firm. The framework is developed and validated in the Indian automotive sector, where the primary data is collected based on perceptions of the respondents working in an automotive company.

LARG metrics can ponder ecological balance, customer satisfaction, associations, effectiveness and sustainability and thus, the study consolidated LARG practices in one umbrella to develop a DSF. The analytical approach under DSF is developed by the integration AHP, DEMATEL, ANP, Extended MOORA and SAW techniques in present study to evaluate a robust supplier under the aegis of LARG practices in SC. DSF is developed by scrutinizing and categorizing LARG characteristics, where the selected LARG characteristics are handled by fuzzy sets theory to deal with the impreciseness and uncertainty in decision making.

The study has identified 63 measures (15 for Lean, 15 for Agile, 14 for resilient and 19 for Green) to support the robust supplier selection process for manufacturing firms. The findings of study explicate “Internal communication agility”, “Interchangeability to personnel resources”, “Manufacturing flexibility”, “degree of online solution”, “Quickness to resource up-gradation”, “Manageability to demand and supply change”, “Overstocking inventory practices” as significant metrics in ranking order. Additionally, “Transparency to share information”, “Internal communication agility”, “Manufacturing Flexibility”, “Green product (outgoing)” are found as influential metrics under LARG practices respectively.

A technical DSF to utilize by the managers is developed, which is connected with knowledge-based theory and a case of an automobile manufacturing firm is presented to illustrate its implementation. The companies can utilize presented DSF to impose service excellence, societal performance, agility and green surroundings in SC for achieving sustainable outcomes to be welcomed by the legislations, society and rivals. The framework represents an important decision support tool to enable managers to overcome imprecise SC information sources.

The study presented a proficient platform to review the most significant LARG alternative in the SC. The study suggested a cluster of LARG metrics to support operational improvement in manufacturing firms for shifting gear toward sustainable SC practices. The present study embraces its existence in enrolling a high extent of collaboration amongst clients, project teams and LARG practices to virtually eradicate the likelihood of absolute project failure.

Cloud computing (CC) services have given a tremendous boost to the creation of efficient and effective solutions. With developing countries at a slow pace of adoption, this research aims to identify factors and their interrelationships influencing the adoption of CC in a developing country context. The developing countries are enjoying numerous benefits from CC services; however, its low adoption is still a question in developing economies; hence, the authors have selected the context of information and communication technology (ICT) firms in India.

The qualitative research method is used where experts from thirteen ICT firms in India are interviewed.

Sixteen factors, twenty-eight subfactors, and 25 interrelationships are revealed through content analysis. Further, causal loop diagrams are proposed to display the behavior of cause and effect of these factors from a system's perspective. This will help to understand the relationships among the factors in order to enhance the speed of CC adoption. Possible financial loss and resistance to change are found as the key barriers to adoption. The proposed interrelationships can guide both policymakers and service providers for designing effective CC policies.

This is the first scholarly work that identifies interrelationships among factors and subfactors, thereby providing a holistic picture to decision-makers while making a choice on whether to adopt cloud services or continue with on premise data centers and servers.

The idea is to propagate the concept of climate resilience in India beyond international mandates and bold statements, enabled through utilization of open data. The research underscores need for climate responsive planning for megacities in India with an example of National Capital Territory of Delhi, the capital of India whose trends and policies often form a blueprint for others to follow.

The research was conducted in six distinct, yet inter-related stages: literature review, data collection, data analysis at four levels – city, zonal, planning division and flood plains inhabited by climate vulnerable population with least adaptive capacity, formulating alternative scenarios of future development, evaluation of scenarios, conclusions and recommendations.

India has approximately 8,000 urban centres. Less than 2% of these centres have a planning document. Less than 1% of these documents acknowledge climate change as a phenomenon let alone a challenge to urban future. It is therefore a priority to address the challenge from a planning perspective for India.

Methodologies for evaluating the multiplier effect are still in their pre-final stage and there exist uncertainties and margin of error.

Aligned with pre-tested methodologies, the research through extensive empirical and spatial-temporal analysis indicates severity and irreversibility of socio-economic and environmental losses.

Risks and vulnerabilities to climate change and climate induced disasters exhibit multiplier effect that varies spatially across a region's demography. Quantitative analysis of multiplier effect on the secondary environment is rarely explored in climate studies. The paper addresses this lacuna by examining climate risks to Indian megacities with a case example of Delhi. The findings suggest that urbanization, climate risks and natural environment are interlinked, where an impact of one generates ripples across other two and their secondary environment plus sectors.

Divorce has negative effects on children, although emotions that children experience after parental divorce are open to different interpretations. Accordingly, this study was conducted to explore loneliness in children of divorce.

A constructivist grounded theory study was carried out through the lens of definitive guidelines provided by Charmaz (2006). The participants were 15 female children aged 11–12 years, who were purposively selected. Data were collected using semi-structured interviews and memos. To analyze data, the authors used four coding techniques, including initial, focused, axial, and theoretical coding. Also, to examine the links between the identified themes, the authors focused on three factors: conditions, actions/interactions, and consequences.

The analysis of the obtained data through the above-mentioned stages led to the identification of three main themes, including parental unavailability, rejection, and mistrust, which shaped children's experience of loneliness through lack of physical access, lack of emotional access, low levels of parental expectations, lack of supervision, absence of belongingness, being ignored, pessimistic views, and insecure relationships.

As was suggested by attachment theory, children of divorce lost their attachment bonds with their parents that intensified their perception of loneliness and negatively affected their social and academic performance. It was revealed that, effects of divorce went beyond the loss of the attachment bonds in families because our participants talked about their relationships with peers and their position in a society, where divorce carries the social stigma and children of divorced mother are marginalized.