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The purpose of the experimental investigation was to optimize the process parameters of the fused deposition modeling (FDM) technique. The optimization of the process was performed to identify the relationship between the chosen factors and the tensile strength of acrylonitrile butadiene styrene (ABS) and carbon fiber polylactic acid (PLA) thermoplastic material, FDM printed specimens. The relationship was demonstrated by using the linear experimental model analysis, and a prediction expression was established. The developed prediction expression can be used for the prediction of tensile strength of selected thermoplastic materials at a 95% confidence level.

The Taguchi L9 experimental methodology was used to plan the total number of experiments to be performed. The process parameters were chosen as three at three working levels. The working range of chosen factors was the printing speed (60, 80 and 100mm/min), 40%, 60% and 80% as the infill density and 0.1mm, 0.2mm and 0.3mm as the layer thickness. The fused deposition modeling process parameters were optimized to get the maximum tensile strength in FDM printed ABS and carbon fiber PLA thermoplastic material specimens.

The optimum condition was achieved by the process optimization, and the desired results were obtained. The maximum desirability was achieved as 0.98 (98%) for the factors, printing speed 100mm/min, infill density 60mm and layer thickness 0.3mm. The strength of the ABS specimen was predicted to be 23.83MPa. The observed strength value was 23.66MPa. The maximum desirability was obtained as 1 (100%) for the factors, printing speed 100mm/min, infill density 60mm and layer thickness 0.2mm. The strength of the carbon fiber PLA specimen was predicted to be 26.23MPa, and the obtained value was 26.49MPa.

The research shows the useful process parameters and their suitable working conditions to print the tensile specimens of the ABS and carbon fiber PLA thermoplastics by using the fused deposition modeling technique. The process was optimized to identify the most influential factor, and the desired optimum condition was achieved at which the maximum tensile strength was reported. The produced prediction expression can be used to predict the tensile strength of ABS and carbon fiber PLA filaments.

The results obtained from the experimental investigation are useful to get an insight into the FDM process and working limits to print the parts by using the ABS and carbon fiber PLA material for various industrial and structural applications.

The results will be useful in choosing the suitable thermoplastic filament for the various prototyping and structural applications. The products that require freedom in design and are difficult to produce by most of the conventional techniques can be produced at low cost and in less time by the fused deposition modeling technique.

The process optimization shows the practical exposures to state an optimum working condition to print the ABS and carbon fiber PLA tensile specimens by using the FDM technique. The carbon fiber PLA shows better strength than ABS thermoplastic material.

The aim of this study is to examine the impact of supply chain management (SCM) practices and retail outlet attributes on the performance of organised food retailers in India during COVID-19 pandemic.

Authors conducted empirical research with SCM practices and retail outlet attributes to evaluate the retailers’ performance. The authors present the results from 321 valid responses from the Indian food retailers. The study used structured equation modeling to present the analysis and the results.

The findings of this study reveal that most of the SCM practices (i.e. information technology, level of information sharing, customer relationship, supplier relationship and goal congruence) have a positive impact on performance except the quality of information sharing. The results show that in the time of the pandemic, the retail outlet attributes (image, service quality and convenience) have no significant relationship with the food retailer’s performance while SCM practices are necessary to achieve better performance of the food retailers.

A proactive approach is needed from retailers at the time of pandemic situations to manage the supply chains. The retailers must be extra careful in screening the suppliers for the short and long run. The reason being that in the situation of pandemic, customers might be more demanding and hence, food retailers need to pay special attention to gain growth. It is also required that the policymakers should give importance to the implementation of these SCM practices to be positioned differently.

The research can be valued in terms of its original contribution towards companies in overcoming the disruption caused by COVID-19 to maintain a balance between demand and supply and proposes a completely new theoretical framework. The proposed theoretical model would add value to the existing literature to help the retailers in process of their performance improvement. The study has provided insights for retail organisations, suppliers and government departments to manage their SCs more effectively and efficiently during the pandemic.

The present study aims to demonstrate the performance assessment of flexible pavement structure in probabilistic framework with due consideration of spatial variability modeling of input parameter.

The analysis incorporates mechanistic–empirical approach in which numerical analysis with spatial variability modeling of input parameters, Monte Carlo simulations (MCS) and First Order Reliability Method (FORM) are combined together for the reliability analysis of the flexible pavement. Random field concept along with Cholesky decomposition technique is used for the spatial variability modeling of the input parameter and implemented in commercially available finite difference code FLAC for the numerical analysis of pavement structure.

Results of the reliability analysis, with spatial variability modeling of input parameter, are compared with the corresponding results obtained without considering spatial variability of parameters. Analyzing a particular three-layered flexible pavement structure, it is demonstrated that spatial variability modeling of input parameter provides more realistic treatment to property variations in space and influences the response of the pavement structure, as well as its performance assessment.

Research is based on reliability analysis approach, which can also be used in decision-making for quality control and flexible pavement design in a given environment of uncertainty and extent of spatially varying input parameters in a space.

The purpose of this study is to identify and prioritize capabilities and practices to ensure a resilient supply chain during an unexpected disruption. In addition, this study ranks maturity factors that influence the main capabilities identified.

This paper is conducted in three stages. First, capabilities and practices are extracted through a literature review. Second, capabilities and practices are ranked using the analytical hierarchical process method. Third, a gray technique for order preference by similarity to ideal solution method is used to rank maturity factors influencing capabilities.

The findings indicate that responsiveness, readiness, flexibility and adaptability are the most important capabilities for supply chain resilience. Also, commitment and communication are the highest maturity factors influencing resilience capabilities.

The findings provide a hierarchical vision of capabilities and practices for industries to increase resilience. Limitations of the paper are related to capabilities, practices and number of experts consulted.

This paper highlights the importance of high-maturity practices in resilience capability adoption. The findings of this study will encourage decisions-makers to increase maturity practices to build resilience against disruption.

The paper reveals that developing powerful capabilities, good practices and a high level of maturity improve supply chain resilience.

The apex planning body of India, NITI Aayog launched an Aspirational District Programme (ADP) in January 2018. The programme aimed to the quick and effective transformation of 112 (14%) districts of the country. This programme is considered as world's biggest result-based governance initiative having reached up to 250 million people. It is based on a ranking that is done on monthly basis. This ranking is based on 49 KPIs across six broad socio-economic themes.

The study attempts to inquire and assess the progress made by 112 Aspirational Districts under Financial Inclusion, Skill Development and Basic Infrastructure theme from the inception of the programme to June 2022 (i.e. 54 months). Instead of ranking districts with delta rank or composite scores, the study divorce from NITI Aayog's methodology of monthly delta ranking. The study explores 8 indicators under the basic infrastructure theme and 16 indicators under the financial inclusion and skill development themes. For this purpose, the study explores the availability of individual household latrines, drinking water, electricity and road connectivity. Districts are also tracked for the number of Internet-connected Gram Panchayats, and panchayats with Common Services. Every district is provided with the target as per national development priority, the study makes an effort to grasp the distance of each district from the national target. This allows researchers to develop a scale Very Far, Far, Near, Very Near, Achieved with descriptive statistics techniques. Juxtaposing the scale with timelines results in a pattern of progress made by these 112 districts.

The purpose of this study is to identify Offshore Wind Energy (OWE) as a key technology that could drive countries toward achieving climate goals. However, there are multiple challenges that this sector faces.

This study aims to identify the challenges faced by the sector globally by systematically reviewing the existing literature in global context and portraying it in the Indian context. Factors are identified using content analysis.

Results suggest high levelized cost of energy as the most discussed challenge for the growth of OWE. Insufficient financial support and policy, initial capital and inadequate technology formed the second, third and fourth most discussed challenges respectively.

To reduce the cost of OWE, the distribution companies in India could adopt feed-in tariffs (FiTs) in the early stages of development and make OWE procurement mandatory. The renewable purchase obligation (RPO) in India is specific to solar and non-solar; policy should accommodate offshore wind-specific RPO targets for each state to reach the 2030 target of 30 GW from OWE.

To the best of the authors’ knowledge, this is the first attempt to study the challenges of OWE development from a global perspective and portray these major challenges in the Indian context and uses content analysis from the existing literature to ascertain the major roadblocks for the development of OWE.

The study identifies the unexplored gap in literature that includes futuristic challenges for OWE from climate change. Future studies can explore the possibilities of forecasting based on climate change scenarios and rank the challenges based on their relevance caused by possible damages.

Current research in the field of behavioural finance has attempted to discover behavioural biases and their characteristics in individual investors’ irrational decision-making. This study aims to find out how biases in information based on knowledge affect decisions about investments.

In step one, through existing research and consultation with specialists, 13 relevant items covering major aspects of bias were determined. In the second step, multiple linear regression and artificial neural network were used to analyse the data of 337 retail investors.

The investment choice was heavily impacted by regret aversion, followed by loss aversion, overconfidence and the Barnum effect. It was observed that the Barnum effect has a statistically significant negative link with investing choices. The research also found that investors’ fear of making mistakes and their tendency to be too sure of themselves were the most significant factors in their decisions about where to put their money.

This research contributes to the expansion of the knowledge base in behavioural finance theory by highlighting the significance of cognitive psychological traits in how leading investors end up making irrational decisions. Portfolio managers, financial institutions and investors in developing markets may all significantly benefit from the information offered.

This research is a one-of-a-kind study, as it analyses the emotional biases along with the cognitive biases of investor decision-making. Investor decisions generally consider the shadowy side of knowledge management.

The objective of the study is to test a conceptual model based on the interrelation between data-driven supply chain quality management practices (DDSCQMP) and the performance of organized retailing firms in India.

Based on a comprehensive review of literature, the dimensions of DDSCQMP concerning the Indian organized retail sector have been extracted. Considering the research objectives, the research data has been collected using a structured questionnaire from Indian retailers. Overall 133 questionnaires were responded successfully from retailers. The model was tested using structured equation modeling (SEM) through PLS 3.0.

The research findings confirm hypotheses and reveal the statistically significant relationship between DDSCQMP and retailers' performance at an aggregate level. However, the results of the individual-level analysis of DDSCQMP appear to vary from practice to practice. Among various DDSCQMP, “customer focus” with the highest beta (ß) value was found to have the greatest impact on performance followed by “employee relations”.

The study provides empirical justification for a structural model that identifies a positive and significant relationship between DDSCQMP and organizational performance within the context of organized retail sector of India.

The purpose of this paper is to understand the role of materialism and brand consciousness in determining the luxury consumption among the young Indian consumers.

In order to measure materialism, brand consciousness, attitude toward luxury brands and purchase intention, pre-established scale items were used to design the self-administered questionnaire. A valid sample of 342 respondents was collected through mall intercepts, in-store intercepts, luxury brands exhibitions and festivals and international airports. The relationship was tested using regression analysis.

The findings support that the materialism and brand consciousness are positively related to the luxury consumption in India and play an important role in predicting the behavior of the young luxury buyers. The Indian youth is buying expensive luxury brands as symbols of status success and wealth in order to fulfill their materialistic goals. The desire to own and possess the well-known and expensive brand names demonstrates the importance the consumers attach to the social and symbolic value of the luxury brands.

The study reveals that the young Indian luxury buyers choose to buy brands that are most advertised. Creative advertisements enhancing luxury brands’ symbolic and social value can be effective. The study has implications for the international luxury brands, as they are expensive, well known and famous among the global consumers.

The key contribution of the study is the establishment of materialism and brand consciousness as important antecedents in the development of attitude toward luxury brands among the young Indian consumers.

This study aims to analyze Open Access (OA) publishing trends and policy perspectives in India. Different aspects, such as the growth of OA journals digital repositories, the proportion of OA availability to research literature and the status of OA mandates and policies are studied.

Data for analyzing OA trends were gathered from multiple data sources, including Directory of Open Access Journals (DOAJ), OpenDOAR, SCImago and Web of Science (WoS) databases. DOAJ and OpenDOAR were used for extracting OA journals and digital repository data. SCImago Journal and Country ranking portal and WoS database were used to obtain Indian publication data for assessing the proportion of OA to research literature. ROARMAP was used to study OA mandates and policies adopted by universities, research institutions and research funders in India. OA mandates and policies of major regulatory bodies and funding agencies were also reviewed using secondary sources of information and related websites.

India ranks number 15 and 17 globally for OA journals and OA repositories, with 317 journals and 98 repositories. Although India’s proportion to OA publications is 23% (7% below the world average of 30%), the annual growth rate of OA publications is around 18%. Although the governing bodies and institutions have made efforts to mandate researchers to adopt OA publishing and self-archiving, its implementation is quite low among Indian researchers, as only three institutions (out of 18 listed in the ROARMAP) are defined the embargo period. Funding agencies in India do not provide financial assistance to authors for the payment of Article Processing Charges despite mandates that research is deposited in OA repositories. India lacks a national OA policy but plans to implement a “one nation one subscription” formula to provide OA to scientific literature to all its citizens.

The study has certain limitations. Because much of India’s research output is published in local journals that are not indexed in WoS, the study recommends conducting further analyses of publications using Scopus and other databases to understand the country’s OA publishing proportion better. A further study based on feedback from different stakeholders through a survey may be conducted for formulating a national OA policy.

The study is the first that used multiple data sources for investigating different facets of OA publishing in India, including OA journals, digital repositories, OA research output and OA mandates and policies for publicly funded research. The findings will be helpful for researchers and policymakers interested in promoting OA adoption among researchers worldwide.