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The purpose of this article is to describe the union databases maintained by the INFLIBNET for university libraries in India. INFLIBNET maintains union databases of serials, books, theses and an “experts” database. Efforts to collect the raw data, maintain it and make it available to the end user via the internet are also discussed.

The article describes the workflow of maintaining union databases and the steps involved are discussed. Various software are being used to provide a systematic approach to these databases and to ensure that the searching for needed documents is user friendly; the user should be able to go automatically to the document supply system with a single click of the mouse button.

If the library system is large, it becomes most important to know the location of documents. The Indian educational system is one of the largest in the world. INFLIBNET maintains union databases of various types of documents for more than 150 university libraries and membership is growing rapidly to accommodate all university and college libraries. Many best procedures on bibliographic standards and guidelines have been adopted and are updated regularly. UniCat, an in house software package has been used to process bibliographic raw data which is then hosted on the website for access by users.

This article is significant to researchers and librarians in India and also more widely.

During pre-vaccine era, pharmaceutical supplies [self-care essentials (SCEs)] have been proved to be a major deflector, protector and safety guard against novel coronavirus disease (COVID-19). Hence, the objective of the study is to provide a comprehensive socio-technological decision-making framework based on multiple criteria for selecting the suppliers of pharmaceuticals, such as SCEs, by multi-brand enterprises (distributors) in the pandemic environment.

A hybrid methodology of Bayesian best worst method (BWM) and multi-attributive border approximation area comparison (MABAC) method has been applied for carrying out the study. Bayesian BWM has been applied for computing the importance of criteria identified for the selection of SCEs' suppliers during pandemic environment and MABAC method evaluated the suppliers of the SCEs.

In the study, the authors have identified eight criteria such as disinfection and sanitization of vehicles, social conscience of suppliers, brand (Technological recognition) of SCEs and logistics and distribution network, among others, which are critical to the selection of a supplier for the supply of SCEs. The application of the proposed hybrid model revealed that lead time and quality of SCEs are of utmost concern for pharmacies in a pandemic environment. Among the ten suppliers, results showed that Suppliers 2, 4 and 5 have been ranked first for supplying hand wash, hand sanitizer and face mask, respectively.

The proposed model has helped the multi-brand distributors of pharmaceuticals in selecting suppliers during the ongoing crisis of COVID-19. In addition to that, in future the outcomes of the study would be helpful for multi-brand distributors as well as pharmacies and hospitals in selecting the best suppliers. Policy makers will be able to make and revise the policies immediately with the help of the proposed decision-making framework.

The paper makes a novel contribution towards theory with the criteria identified for selecting best suppliers during the pandemic COVID-19. Additionally, the proposed hybrid model helps multi-brand distributors of pharmaceuticals in making decisions that lead to a huge social and economic success in pandemic time.

Entrepreneurship across sectors has been impacted by the paradigm of open innovation in the last few decades. Although Open Innovation is argued to impact firm performance the strategic building blocks of open innovation are not discussed in the prior literature. This study aims to conceptualize open innovation and identify the antecedents and outcomes of open innovation.

Using a qualitative study based on open-ended essays solicited from 47 SMEs and startups based out in Europe and the USA, the authors propose an overarching conceptual framework using a theoretical sampling approach adopted to establish data saturation and data analysis was carried out using thematic coding. Market place evidence was used for triangulation of the authors’ research framework and to establish the validity of the constructs.

Building on the entrepreneurial bricolage theory, this study proposes bricolage and Platformization of innovations as antecedents to open innovation. The study also conceptualizes open innovation by identifying three underlying dimensions for open innovation. Next, the study proposes a positive association between open innovation and firm performance. Finally, the authors discuss relevant implications with future research directions of the study.

The practical implication is the development of a sustained competitive advantage enhancing framework for entrepreneurial ventures with the help of open innovation.

With the application of the developed framework for the entrepreneurial ventures, a set of strategic activities related to open innovation can be proposed that would help these ventures to enhance their innovation and marketing capabilities, thereby helping them with a sustained competitive advantage. The present study would also help the policymakers to frame policies that help the firms with a shift toward open innovation.

This study aims to “identify”, “analyse” and “categorise” the lean-sustainability enablers for start-ups during the COVID-19 epidemic using total interpretive structural modelling (TISM).

A closed-ended questionnaire was used to collect data in addition to the scheduled interview. The TISM methodology is used to determine how the variables interact, and the matrice d’Impacts croises-multiplication applique´ a classement (MICMAC) method is used to rank and categorise the lean-sustainability enablers.

This study identified ten lean-sustainability enablers for start-ups during the COVID-19 pandemic. The study says that the key factors are leadership and managerial commitment, implementation of employee skills and abilities, strategic need, personnel engagement and financial ability.

The study focused primarily on lean-sustainability characteristics for start-ups.

This research will aid key stakeholders and academics in better understanding the factors that contribute to lean-sustainability in start-ups.

This study proposes the TISM technique for start-ups, which is a novel attempt in the subject of lean-sustainability in this industry.

The purpose of this study is to examine the thermo-hydrodynamic performance of tilted non-circular journal bearings lubricated with a micropolar fluid. The investigated bearing types are two- and three-lobe journal bearings with finite length.

For this purpose, modified Reynolds, energy and three-dimensional Laplace equations are solved numerically by using generalized differential quadrature method. The effects of micropolarity characteristics of lubricants, such as characteristic length and coupling number, as well as tilt angle as a design parameter, on the performance of non-circular two- and three-lobe journal bearings are studied.

The results show that the tilt angle can affect the temperature and pressure profiles causing variation in the performance of non-circular bearings. Increasing coupling number and decreasing characteristic length cause the load-carrying capacity to decrease because of the increase in maximum oil temperature of the fluid film of lubricant and decrease in the minimum oil base viscosity. So, it is possible to select suitable values of tilt angle for achieving optimum performance of these bearings.

The non-circular bearings suggest several design parameters such as tilt angle for designers. By considering thermal effects for micropolar lubricant, the requirements of a specific application can be fulfilled.

The purpose of this study is the identification and analysis of key ethical issues of green procurement (GP) and the potential solutions to mitigate the issues in the Indian automobile sector.

Based on the literature review and expert elicitation, 23 ethical issues of GP in the Indian automobile industry and 11 solutions to mitigate these issues were identified. This paper explores the ethical issues based on an integrated method consisting of interpretative structural modelling fuzzy Matrice d'Impacts Croisés-Multiplication Appliquée á un Classement, analytical hierarchy process and the solutions to mitigate these issues using fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje.

The findings suggest that ethical issues such as favouritism towards suppliers and failure to fulfil business objectives by top management are identified as the most significant variables with the highest importance weights, while top management commitment for ethical behaviour is identified as the most potent solution for mitigating the issues.

This study is limited to the literature review and experts’ opinions.

The results may help practitioners and researchers to focus on major ethical issues of GP to strategize proactive solutions that may help to mitigate or eliminate the ethical issues.

This paper is an original contribution of the analysis of GP and provides an interesting insight into the Indian automotive industry.

In developing countries such as India, start-ups play an essential role in “industrial output,” “Gross Domestic Product ” and “employment creation.” Evidence suggests that pandemics have risen over the last century due to rising global travel and assimilation, urbanization, alterations in land use, and significantly larger exploitation of the natural environment. These trends are likely to continue and intensify. These pandemic episodes affect businesses, especially start-ups. Supplier selection is among the vital critical elements that start-ups must include in start-ups' strategy procedures during the pandemic episodes. This study's focus is to “identify,” “analyze,” and “categorize” the factors affecting supplier selection in start-ups during frequent pandemic episodes like coronavirus disease 2019 (COVID-19).

Through “literature review” and “experts' opinion” from various start-ups in India, ten affecting factors were identified. Total Interpretative Structural Modeling (TISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) were employed to analyze the interrelationship among the factors affecting the supplier selection on start-ups during frequent pandemic episodes, and these factors were ranked as “autonomous,” “independent,” “linkage,” and “dependent” factors.

The findings show that “performance history,” “service levels,” “technical capability,” and “financial stability” are the most critical factors affecting the supplier selection on start-ups during frequent pandemic episodes. The next importance should be safety and environmental concern” and “quality.”

The factors affecting supplier selection on start-ups during frequent pandemic episodes are the current focus of this study. This study is mainly performed on Indian start-ups and can be extended to other countries.

The start-ups can rely on this study to clearly understand the factors affecting the supplier selection on start-ups during frequent pandemic episodes.

There is no research regarding factors affecting supplier selection on start-ups during the COVID-19 emergencies. This research gap is filled by analyzing aspects linked to supplier selection in start-ups. This gap inspired the present study, which employs the “Total Interpretive Structural Modeling (TISM)” technique to uncover supplier selection determinants and investigate hierarchical interconnections among factors influencing/affecting supplier selection in start-ups during frequent pandemic episodes.

This paper aims to identify, examine, and present an empirical research design of behavioral finance of potential investors during Covid-19.

A well-structured questionnaire was designed; a survey was conducted among potential investors using convenience sampling, and 200 valid responses were collected. The research work uses multiple regression and discriminant function analysis to evaluate the influence of cognitive factors on the financial decision-making of investors.

Recency and familiarity bias are proven to have the highest significant impact on the financial decisions of investors followed by confirmation bias. Overconfidence bias had a negligible effect on the decision-making process of the respondents and found insignificant.

Covid-19 is a temporary phase that may lead to changes in financial behavior and investors’ decisions in the near future.

The paper will help academicians, scholars, analysts, practitioners, policymakers and firms dealing with capital markets to execute their job responsibilities with respect to the cognitive bias in terms of taking financial decisions.

The present investigation attempts to fill the gap in the literature on the intended topic because it is evident from literature on the chosen subject that no study has been undertaken to evaluate the impact of cognitive biases on financial behavior of investors during Covid-19.

The purpose of this paper is to study and develop supply chain structure of traditional Indian agri-fresh food supply chain (AFSC). This paper proposes a mathematical model to design a traditional Indian AFSC to minimize total distribution cost and post-harvest losses in the chain.

This paper formulates two mathematical models to structure and represent the flow of products in the existing chain. First, a three-echelon, multi-period, multi-product, mixed-integer linear programming (MILP) model is formulated to minimize the total distribution cost incurred in the chain. Further, the developed formulation is extended by considering the perishability of products in the second model.

A real case study problem of Mandsaur district (India) is solved in LINGO 17.0 package to check the validity of the formulated models. The perishable (second) model of AFSC reports better results in terms of costs and post-harvest losses minimization. The results revealed that 92% of the total distribution cost incurred in the transportation of products from farmers to the hubs.

This paper includes implications for redesigning an existing supply chain network by incorporating an appropriate transportation strategy from farmers to hubs to minimize transportation inefficiency and enhance the profitability of farmers.

The formulated AFSC model would help managers and policymakers to identify optimal locations for hubs where required infrastructure would be developed.

According to the author's best knowledge, this paper is the first to design traditional Indian AFSC by considering the perishability of products.

This research aims to describe the influence of weight per cent of graphite (Gr), applied load and sliding speed on the wear behavior of aluminum (Al) alloy A356 reinforced with silicon carbide (SiC) (10 Wt.%) and Gr (1 Wt.% and 5 Wt.%) particles. The objective is to analyze the effect of the aforementioned parameters on a specific wear rate.

These hybrid composites are obtained by means of the compo-casting process. Tribological analyses were conducted on block-on-disc tribometer at three different loads (10, 20 and 30 N) and three different sliding speeds (0.25, 0.5 and 1 m/s), at the sliding distance of 900 m, in dry sliding wear conditions. Optimization of the tribological behavior was conducted via the Taguchi method, and ANOVA was used for the analysis of the specific wear rate. Confirmation tests are used to foresee and check the experimental results. Examined samples were analyzed via a scanning electron microscope (SEM). Regression models for predicting specific wear rate were developed with Taguchi and ANN (artificial neural network) methods.

The biggest impact on value of specific wear rate has the load (43.006%), while the impact of Wt.% Gr (31.514%) was less. After comparison of the results, i.e. regression models, for predicting the specific wear rate, it was observed that ANN was more efficient than the Taguchi method. The specific wear rate of Al alloy A356 with SiC (10 Wt.%) and Gr (1 Wt.% and 5 Wt.%) decreases with a decrease in the load and weight per cent of Gr-reinforcing material, as well as with a decrease in sliding speed.

The results obtained in this paper using the Taguchi method and the ANN method are useful for improving and further investigating the wear behavior of the SiC- and Gr-reinforced Al alloy A356.