International Journal of Innovation Science

Chaudhari, Sagar Lotan; Sinha, Manish

2021 International Journal of Innovation Science

doi: 10.1108/ijis-09-2020-0156

India ranks third in the global startup ecosystem in the world incubating more than 50,000 startups and witnessing 15% YoY growth per year. Being a center of innovation and skilled labor, Indian startups have attracted investments from all over the world. This paper aims at exploring the trends that are driving the growth in the Indian startup ecosystem.Design/methodology/approachTop 200 startups according to valuation are selected as a sample to find out the major trends in the Indian startup ecosystem. This paper includes surveying the sample startups about the implementation of trends such as big data, crowdfunding and shared economy in their startup and its tangible, as well as intangible impacts on their business. The result of the survey is analyzed to get an overview of the emerging trends in the Indian startup ecosystem.FindingsMajor ten emerging trends that drive growth in the Indian startup ecosystem are discovered and the areas where these trends can be leveraged are identified.Originality/valueThis research has contributed toward structuring and documenting the growth driving trends, and it will help the budding entrepreneurs to get familiar with the contemporary trends, pros and cons associated with it and the ways to leverage these trends to build a successful startup.

Shahi, Chinmay; Sinha, Manish

2021 International Journal of Innovation Science

doi: 10.1108/ijis-09-2020-0157

Digital transformation is the way forward for all businesses. The technology is advancing at a rapid pace and the companies need to adapt to the change, not just to take advantage of the enormous opportunities it provides but even to stay relevant in this volatility, uncertainty, complexity, and ambiguity world. This study aims to define the concept of digital transformation and what it means in today’s business scenario. It helps to understand the different stages of digital maturity, identify the barriers in adopting different technologies and provide solutions to overcome those challenges.Design/methodology/approachThis is a qualitative study in which opinions of the digital transformation experts were collected using a qualitative questionnaire. Natural language processing (NLP) and text mining techniques were applied along with a thorough analysis of the text to generate the results.FindingsThe study was able to uncover – what it means to be digitally transformed, different challenges an organization faces during the digital transformation journey and their potential solutions.Originality/valueThe existing literature on the topic is scattered and does not provide a roadmap for a company to adopt digital transformation. This study aims to fill up the gap and cover various aspects of the whole transformation process. The uniqueness of the study lies in the use of NLP techniques to perform text analytics on the data.

Pradhan, Vishal; Bhattacharya, Sonali

2021 International Journal of Innovation Science

doi: 10.1108/ijis-09-2020-0168

Researchers have studied processes of improving road traffic-safety culture by explicitly evaluating the socio-psychological phenomenon of traffic-risk. The implicit traffic-system cues play an important role in explaining urban traffic-culture. This paper aims to ascertain an interpretive framework of the alternative processes of road traffic safety culture is antecedent to promote traffic-safety behaviour in Indian urban context. Subsequently, the authors discussed the reasons for those relationships exists.Design/methodology/approachFour experts of the urban traffic-safety domain participated in total interpretive structural modelling (TISM) study by completing an interpretive consensus-driven questionnaire. The drafted interpretive model was evaluated for road users proactive action orientation about the traffic-safety decision.FindingsThe evolved directed graph (digraph) of the culture of urban traffic-safety management was a serial three-mediator model. The model argued: In the presence of traffic-risk cues, people may become apprised to safety goals that initiate traffic-safety action. Consequently, expectancy-value evaluation motivates the continuation of traffic-safety intention that may lead to the implementation of adaptation plan (volitional control), thus habituating road users to traffic-safety management choice.Practical implicationsThe modellers of traffic psychology may empirically estimate and test for the quality criteria to ascertain the applicability of the proposed mechanism of urban traffic-safety culture. The decision-makers should note the importance of arousal of emotions regarding traffic-risk, reduce the impact of maladaptive motivations and recursively improve control over safety actions for promoting safety interventions.Originality/valueThe authors attempted to induce an interpretive model of urban traffic-safety culture that might augment extant discussion regarding how and why people behave in an urban traffic system.

Koul, Shiva; Ambekar, Suhas Suresh; Hudnurkar, Manoj

2021 International Journal of Innovation Science

doi: 10.1108/ijis-09-2020-0174

The purpose of this paper is to determine, rank and form composite relational factors that impact the millennial consumer’s mind-set when they opt for an access-based subscription of an over-the-top (OTT) platform service. In the competitive rising Indian market of OTT platforms, there is a need to understand what factors drive the subscription of a service for a company strategizing to build up on their customer base or for a company seeking to retain its customers.Design/methodology/approachThe approach includes determining factors that impact the buying behavior of the consumer and have them ranked by the survey participants in order of their importance as a factor in considering a subscription of an OTT platform service. Questionnaire as a method is used for primary data collection in this research. Using “purposive sampling,” participants of the survey were determined based on their age group and current or historic consumption of at least one OTT platform service. The survey was conducted for the millennial viewership from Tier I and Tier II cities that have good internet connectivity over their mobile phones.FindingsThe result of this research is a ranking of factors based on their importance as perceived by the millennial consumers and then form composite factors, which have similarities in responses.Practical implicationsThis research enables the consumers of the information to dwell on the factors that prove to be of comparative importance to the consumer and plan/forecast their strategies and further research studies accordingly.Originality/valueA research along similar lines has been conducted for US-based OTT platforms. However, this research is specific for Indian consumers and platforms and holds significance because of growth in the Indian OTT market.

Thakkar, Kushalkumar; Ambekar, Suhas Suresh; Hudnurkar, Manoj

2021 International Journal of Innovation Science

doi: 10.1108/ijis-09-2020-0172

Longitudinal facial cracks (LFC) are one of the major defects occurring in the continuous-casting stage of thin slab caster using funnel molds. Longitudinal cracks occur mainly owing to non-uniform cooling, varying thermal conductivity along mold length and use of high superheat during casting, improper casting powder characteristics. These defects are difficult to capture and are visible only in the final stages of a process or even at the customer end. Besides, there is a seasonality associated with this defect where defect intensity increases during the winter season. To address the issue, a model-based on data analytics is developed.Design/methodology/approachAround six-month data of steel manufacturing process is taken and around 60 data collection point is analyzed. The model uses different classification machine learning algorithms such as logistic regression, decision tree, ensemble methods of a decision tree, support vector machine and Naïve Bays (for different cut off level) to investigate data.FindingsProposed research framework shows that most of models give good results between cut off level 0.6–0.8 and random forest, gradient boosting for decision trees and support vector machine model performs better compared to other model.Practical implicationsBased on predictions of model steel manufacturing companies can identify the optimal operating range where this defect can be reduced.Originality/valueAn analytical approach to identify LFC defects provides objective models for reduction of LFC defects. By reducing LFC defects, quality of steel can be improved.

Kulkarni, Suraj; Ambekar, Suhas Suresh; Hudnurkar, Manoj

2021 International Journal of Innovation Science

doi: 10.1108/ijis-09-2020-0175

Increasing health-care costs are a major concern, especially in the USA. The purpose of this paper is to predict the hospital charges of a patient before being admitted. This will help a patient who is getting admitted: “electively” can plan his/her finance. Also, this can be used as a tool by payers (insurance companies) to better forecast the amount that a patient might claim.Design/methodology/approachThis research method involves secondary data collected from New York state’s patient discharges of 2017. A stratified sampling technique is used to sample the data from the population, feature engineering is done on categorical variables. Different regression techniques are being used to predict the target value “total charges.”FindingsTotal cost varies linearly with the length of stay. Among all the machine learning algorithms considered, namely, random forest, stochastic gradient descent (SGD) regressor, K nearest neighbors regressor, extreme gradient boosting regressor and gradient boosting regressor, random forest regressor had the best accuracy with R2 value 0.7753. “Age group” was the most important predictor among all the features.Practical implicationsThis model can be helpful for patients who want to compare the cost at different hospitals and can plan their finances accordingly in case of “elective” admission. Insurance companies can predict how much a patient with a particular medical condition might claim by getting admitted to the hospital.Originality/valueHealth care can be a costly affair if not planned properly. This research gives patients and insurance companies a better prediction of the total cost that they might incur.

Sridhar, Vivek; Bhattacharya, Sanjay

2021 International Journal of Innovation Science

doi: 10.1108/ijis-09-2020-0171

The purpose of this study is to find out the significant factor/s relating to an information technology (IT) employee’s household that determines the job effectiveness of an employee.Design/methodology/approachThe approach involves surveying IT employees from across levels of work-experience, companies and cities on household factors that affect their job effectiveness while they work from home and uses discriminant analysis to find out important factor/s that determines if an employee’s job effectiveness remains constant or is better at the workplace that at home.FindingsThe number of elderly staying in the house, age of the eldest member of the household, observable power cuts at home and number of cars owned by individuals were found to be significant factors affecting an IT employees’ job effectiveness.Originality/valueThe study targets a very niche area of the impact of household factors on an IT employee. The findings of this research enable IT organizations from India with insights and enable them to come up with innovative interventions to manage employees on a personalized basis to improve an employees’ job effectiveness and drive organizational effectiveness on a whole, during and post the COVID-19 pandemic.

Ambekar, Suhas Suresh; Deshmukh, Umesh; Hudnurkar, Manoj

2021 International Journal of Innovation Science

doi: 10.1108/ijis-10-2020-0182

The study aims to establish an impact of supplier relationship and information and communication technology through purchasing practices on firm performance.Design/methodology/approachReview of relevant literature resulted in constructs, namely, supplier relationships, information and communication technology, purchasing practices and firm performance. A survey of 179 manufacturing companies through structured questionnaire was conducted. The responses were analysed through structural equation modelling using the partial least squares method.FindingsIt is observed that the firm performance is directly influenced by purchasing practices and indirectly by supplier relationships and information technology. The use of information technology in materials management affects supplier relationships and purchasing practices both.Practical implicationsThe study provides a model for purchasing practitioners by highlighting the importance of supplier relationship management. Though the firms are running after improving technology, it can only affect firm performance through proper purchasing practices.Originality/valueThe study provides empirical evidence to the practical notions that exist in purchasing practitioners.