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In the Indian manufacturing SMEs context, supply chains have a complex structure having multiple echelons, multiple partners and multiple locations. Due to these complexities, most of the Indian manufacturing SMEs face several types of supply chain risks. This paper aims to identify the dominant risk variables and to develop the interrelationship among these risk variables.

Based on the literature review and experts’ opinion, nine dominant risk variables faced by an Indian manufacturing SMEs have been identified. An interpretive structural modelling (ISM) approach has been adopted to establish the interrelationship among the risk variables. These risk variables have been classified by using MICMAC analysis. Based on ISM-MICMAC approach, a case study on three Indian manufacturing SMEs has been carried out.

This study would help the supply chain managers to understand and prioritize the significant risk variables. Nine significant risks variables of Indian manufacturing small and medium enterprises (SMEs) have been studied. External risk, information technology risk and financial risk have identified as most influencing risk variables, while delay risk and market risk have emerged as the most dependent risk variables. These results will provide a guideline to supply chain managers for implementation of supply chain risk management (SCRM).

In this study, an ISM-based model is developed based on the opinion of experts from a group of Indian manufacturing SMEs; as such, this model may be biased and limited to a selected company. This framework can be extended further by adding more risk variables and sub-risk variables from the other sectors/organizations.

Many SCRM models are available in past literature, but no model has been proposed for the Indian Manufacturing SMEs. This research finding can be useful for managers to understand the characteristics and interrelationships among the risk variables for building a robust supply chain. These results will also help the supply chain managers in making proactive plans for SCRM, especially in the Indian SMEs context.

The purpose of this paper is to present an analytical study for a problem of unsteady free convection boundary layer flow past a periodically accelerated vertical plate with Newtonian heating (NH).

The equations governing the flow are studied in the closed form by using the Laplace transform technique. The effects of various physical parameters are studied through graphs and the expressions for skin friction, Nusselt number and Sherwood number are also derived and discussed numerically.

It is observed that velocity, concentration and skin friction decrease with the increasing values of Sc whereas temperature distribution decreases in the increase in Pr in the presence of NH.

This study is limited to a Newtonian fluid. This can be extended for non-Newtonian fluids.

Heat and mass transfer frequently occurs in chemically processed industries, distribution of temperature and moisture over agricultural fields, dispersion of fog and environment pollution and polymer production.

Free convection flow of coupled heat and mass transfer occurs due to the temperature and concentration differences in the fluid as a result of driving forces. For example, in atmospheric flows, thermal convection resulting from heating of the earth by sunlight is affected differences in water vapor concentration.

The authors have studied heat and mass transfer effects on unsteady free convection boundary layer flow past a periodically accelerated vertical surface with NH, where the heat transfer rate from the bounding surface with a finite heat capacity is proportional to the local surface temperature, and which is usually termed as conjugate convective flow. The equations governing the flow are studied in the closed form by using the Laplace transform technique. The effects of various physical parameters are studied through graphs and the expression for skin friction also derived and discussed.

Sentiment analysis has observed a nascent interest over the past decade in the field of social media analytics. With major advances in the volume, rationality and veracity of social networking data, the misunderstanding, uncertainty and inaccuracy within the data have multiplied. In the textual data, the location of sarcasm is a challenging task. It is a different way of expressing sentiments, in which people write or says something different than what they actually intended to. So, the researchers are showing interest to develop various techniques for the detection of sarcasm in the texts to boost the performance of sentiment analysis. This paper aims to overview the sentiment analysis, sarcasm and related work for sarcasm detection. Further, this paper provides training to health-care professionals to make the decision on the patient’s sentiments.

This paper has compared the performance of five different classifiers – support vector machine, naïve Bayes classifier, decision tree classifier, AdaBoost classifier and K-nearest neighbour on the Twitter data set.

This paper has observed that naïve Bayes has performed the best having the highest accuracy of 61.18%, and decision tree performed the worst with an accuracy of 54.27%. Accuracy of AdaBoost, K-nearest neighbour and support vector machine measured were 56.13%, 54.81% and 59.55%, respectively.

This research work is original.

To enhance the performance of hydrostatic bearings, graphene serves as a lubricant additive. Using the high thermal conductivity of graphene, the purpose of this study is to focus on the impact of graphene nano-lubricating oil hydrostatic bearing temperature rise at various speeds and eccentricities.

The thermal conductivity of graphene nano-lubricating oil was calculated by molecular dynamics method and based on the viscosity–temperature effect, the coupled heat transfer finite element model of hydrostatic bearing was established; temperature rise of pure lubricating oil and graphene nano-lubricating oil hydrostatic bearing were analysed at different speed and eccentricity based on computational fluid dynamics method.

With the increase of speed and eccentricity, the temperature rise of 0.2% graphene nano-lubricating oil bearings is lower than that of pure lubricating oil bearings; in addition with the increase of graphene mass fraction, the temperature rise of graphene nano-lubricating oil bearings is always higher than that of pure lubricating oil bearings, and the higher the speed, the more obvious the phenomenon.

The effects of graphene as a lubricant additive on the thermal conductivity of nano-lubricating oil and the variation of the temperature rise of graphene nano-lubricating oil bearings compared to pure lubricating oil bearings were analysed by combining micro and macro methods.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0388

The paper develops a model for enhancing R&D productivity for Indian public funded laboratories. The paper utilizes the productivity data of five Council of Scientific and Industrial Research (CSIR) laboratories for analysis and to form the constructs of the model.

The weighted average method was employed for analyzing the rankings of survey respondents pertaining to the significant measures enhancing R&D involvement of researchers and significant non-R&D jobs. The authors have proposed a model of productivity. Various individual, organizational and environmental constructs related to the researchers working in the CSIR laboratories have been outlined that can enhance R&D productivity of researchers in Indian R&D laboratories. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to find the predictability of the productivity model.

The organizational factors have a crucial role in enhancing the R&D outputs of CSIR laboratories. The R&D productivity of researchers can be improved through implementing the constructs of the proposed model of productivity.

The R&D productivity model can be adapted by the R&D laboratories to enhance researchers’ R&D involvement, increased R&D outputs and achieving self-sustenance in long run.

The R&D laboratories can initiate exercises to explore the most relevant factors and measures to enhance R&D productivity of their researchers. The constructs of the model can function as a guideline to introduce the most preferable research policies in the laboratory for overall mutual growth of laboratory and the researchers.

Hardly any studies have been found that have focused on finding the measures of enhancing R&D involvement of researchers and the influence of significant time-intensive jobs on researchers’ productivity.

Soil is an essential component of road construction and is used in the form of subgrade materials. It ensures the stability and durability of the road under adverse conditions; being one of the important parameters, poor judgment of the engineering properties of soil can lead to pavement failure. Geopathic stress (GS) is a subtle energy in the form of harmful electromagnetic radiation. This study aims to investigate the effect of GS on soil and concrete.

A total of 23 soil samples from stress zones and nonstress zones were tested for different engineering properties like water content, liquid limit, plastic limit, specific gravity and California bearing ratio. Two concrete panels were placed on GS zones, and their quality was monitored through nondestructive testing for a period of one year.

The result shows that the engineering properties of soil and pavement thickness are increasing in stress zones as compared with nonstress zones. For concrete panels, as time passes, the quality of the concrete gets reduced, which hints toward the detrimental effect of GS.

This research is a systematic, scientific, reliable study which evaluated subgrade characteristics thus determining the detrimental impact of the GS on soil and pavement thickness. On a concluding note, this study provides a detailed insight into the performance of the road segment when subjected to GS. Through this investigation, it is recommended that GS should be considered in the design of roads.

Innovation and entrepreneurship are regarded as the key drivers to steer the engine of economic development in any nation. As a result, to understand the context and process of innovation and entrepreneurship there has been a steady rise in scientific literature and empirical studies. The purpose of this paper is to study the trends and progress of academic research on innovation and entrepreneurship in India by identifying the key articles, journals, authors and institutions.

Scientometric methods especially bibliometrics is used, for measuring the maturity of this research field in the country. The paper studies the research landscape in innovation and entrepreneurship in India by doing a bibliometric analysis using data from publications indexed in the Scopus database from the year 2000 to 2018. The study takes a multidisciplinary review of the literature in innovation and entrepreneurship research in India and could be used as a reference for future studies in this theme.

The study finds an increase in the scholarly studies in innovation and entrepreneurship in India in the last decade. It was also found that a large number of publications were joint-authored and collaborations between Indian and foreign universities is happening. The paper also highlights the authorship patterns, top journals and the most cited papers.

A major limitation of this study is that it has considered publications which are indexed in Scopus. This paper has contributed by highlighting the growth of studies in the field of innovation and entrepreneurship in the Indian context. The results can be used by future studies in this area as a starting point to highlight the nature of this research area.

The study attempts to present a trend analysis of published literature on innovation and entrepreneurship in India.

Strategy.

This case can be used on a strategic management course in the second year of an MBA programme, any special elective course on the media and entertainment industry and in executive education programmes to demonstrate the application of strategic management concepts and frameworks.

The Indian film industry was the largest in the world and the seventh largest in terms of revenue. Significant number of movies were made in languages such as Bengali, Marathi, Telugu, Tamil, Malayalam and Kannada, with Hindi commanding the highest number. The film industry in Karnataka made movies in the Kannada language. The industry was plagued by a host of issues with the industry contributing just 2 per cent of the revenues and box office success rate at just around 25 per cent. The state government had set up Karnataka Chalanachitra Academy with the objective of promotion and development of the movie industry in Karnataka. The Chairman of the academy, Shailesh Singh, was extremely concerned about the poor success rate of Kannada movies and was contemplating various options of reviving the ailing Kannada movie industry.

The expected learning outcomes are as follows: application of strategic management frameworks in the context of the movie industry; analysis of industry issues from the long-term and short-term perspectives; study of different entities in the movie industry and the roles they play and their interdependence; applying learning to suggest survival strategies in an extremely competitive market; and insights into the role of government in the media/entertainment industry.

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CSS 11: Strategy.