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Traditionally, loan officers use different credit scoring models to complement judgmental methods to classify consumer loan applications. This study explores the use of decision trees, AdaBoost, and support vector machines (SVMs) to identify potential bad loans. Our results show that AdaBoost does provide an improvement over simple decision trees as well as SVM models in predicting good credit clients and bad credit clients. To cross-validate our results, we use k-fold classification methodology.

The purpose of this paper is to present a comprehensive framework for quality-related performance measures linked to supply chain risk (SCR) by analyzing and framing them into a hierarchical structure.

In this paper, quality-related performance measures (QM) are identified on the basis of literature survey and expert opinion. The quality measures are formulated as hierarchy structure and fuzzy AHP as a multi attribute decision-making tool is applied to judge the viable candidates.

Based on a fuzzy AHP approach, a revised risk matrix with a continuous scale was proposed to assess the QMs’ classes. The result classifies the QMs in different categories (extreme, high, medium and low). Based on this result, some management implications and suggestions are proposed.

The present work proposes an assessment methodology for quality-related performance measures linked to SCR. The revised risk matrix with continuous scale for risk assessment in this field is a novel approach. This study contributes to the supply chain management and quality management literature, and provides suggestions for managers to adopt different strategies for different risk classes.

Social enterprises (SEs) have experienced unprecedented uncertainty due to COVID-19, and it has challenged the fundamental assumptions underlying the SEs. Little is known about the strategic response of SEs when their fundamental characteristics are being challenged. The purpose of this paper is to explore – how do SEs respond to a crisis caused by the pandemic?

This paper adopts a case study approach and reports the response strategy of impulse social enterprises (ISE) from India. Data were collected through interviews, Webinars and organizational reports. To analyze the data, the authors examined the fundamental assumption on SE that was challenged by the pandemic.

The response strategy of ISE is driven by social and substantive rationality focusing on the relationship with the community and doing what is good for them. The role of communication was vital in gathering support and resources to continue with their function. ISE adapted a mindset of mission agility and created an alternative market for its product.

This study highlights the response strategy of SE in an emerging economy like India, which experienced one of the stringent lockdowns. It is probably one of the few studies that examined the responses of SE under a crisis that challenged their fundamental attributes by adopting the framework of Bacq and Lumpkin (2021).

The purpose of this paper is to model and investigate collaborative culture and relationship strength roles in supply chain collaboration. This research highlights critical role played by culture and relationship strength in collaboration.

Drawing from relational view, a conceptual model is developed with the help of literature, and the model is validated with data collected in India using partial least squares method.

Results and analyses revealed that culture and relationship strength significantly and strongly influence each collaborative activity. The relationship strength fully mediates between collaborative culture and supply chain performance. The research also finds that the relationship strength partially mediates between collaborative culture and market-based information sharing, operational resource planning and sharing. In the long-term, collaborative culture drives relationship strength and the element enhances collaborative activities.

This research attempted to explore collaborative culture and relationship strength which are crucial for collaborative relationship. Many mediation effects are studied which increase the understanding and give insights for its implementation. Its theoretical and practical implications are highlighted. This knowledge has enough potential to lead collaborative relationships towards success.

The “war for talent” is not limited to developed economies but has become a common feature in emerging economies such as India. From the sociocultural perspective, India represents one of the oldest cultural heritages with distinct cultural values. The cultural difference may contribute to explain organizational practices toward talent retention. In the present chapter, the authors focus on the institutional, legal, and cultural context and highlight their uniqueness with respect to the Indian context. Within the institutional context, the authors found that prior to liberalization (which happened in 1990s), the Indian business scene was dominated by public firms or a small enclave of private firms. For both types of organization, turnover hardly mattered, and turnover was indeed negligible. Employees saw firms as “employers for life”: in such a context, voluntary turnover was extremely rare. Further, in the early legal context, it was hard for any private firm to “fire” an employee. Therefore, involuntary turnover was close to nil as well. Things began to change post-liberalization when the Indian scene was dominated by an influx of private players. The Indian mind too accepted turnover to be a part of the corporate life. In the present chapter, the authors provide a snapshot of what, why, and how of employee turnover in the Indian context. The authors specifically focus on what motivates employees to remain with the organization or why do they leave the organization. The authors close the chapter with insights relevant to both academicians and practitioners.

Recent multichannel research suggests that consumers use multiple channels to reap attribute-based benefits which have led to showrooming phenomenon. The purpose of this paper is to investigate the reasons for consumers’ showrooming behaviour and propose a comprehensive model based on application and extension of the “Theory of planned behaviour”.

Using the probability sampling approach, 278 complete responses were obtained via web-based surveys for analysing the showrooming behaviour. The research model was tested using the “Partial least squares method” which follows a variance-based structural equation modelling approach.

The results of the study indicate that “touching and feeling the product” and “sales staff assistance” motivated customers to visit the physical store before buying online. “Better online service quality” and “lower prices online” induced customers to later purchase online. Price conscious customers and those with the ability to use multiple channels were more likely to engage in showrooming behaviour.

The generalization of the findings may be limited because the data were collected from a small sample size. The subject calls for more extensive research for drawing generalizations due to lack of the substantive literature on the core area of study.

The model proposed will help retailers in understanding the showrooming phenomenon which recent researchers have considered as a threat to retail. The study provides basis for devising strategies to defend showrooming customers.

This paper adds to the body of knowledge in retailing by proposing a model on showrooming which is an emerging area of research in the present retail landscape.

The purpose of this paper is to use Twitter analytics for analyzing the startup ecosystem of India.

The paper uses descriptive analysis and content analytics techniques of social media analytics to examine 53,115 tweets from 15 Indian startups across different industries. The study also employs techniques such as Naïve Bayes Algorithm for sentiment analysis and Latent Dirichlet allocation algorithm for topic modeling of Twitter feeds to generate insights for the startup ecosystem in India.

The Indian startup ecosystem is inclined toward digital technologies, concerned with people, planet and profit, with resource availability and information as the key to success. The study categorizes the emotions of tweets as positive, neutral and negative. It was found that the Indian startup ecosystem has more positive sentiments than negative sentiments. Topic modeling enables the categorization of the identified keywords into clusters. Also, the study concludes on the note that the future of the Indian startup ecosystem is Digital India.

The analysis provides a methodology that future researchers can use to extract relevant information from Twitter to investigate any issue.

Any attempt to analyze the startup ecosystem of India through social media analysis is limited. This research aims to bridge such a gap and tries to analyze the startup ecosystem of India from the lens of social media platforms like Twitter.

Demand for Geopolymer concrete (GPC) has increased recently because of its many benefits, including being environmentally sustainable, extremely tolerant to high temperature and chemical attacks in more dangerous environments. Like standard concrete, GPC also has low tensile strength and deformation capacity. This paper aims to analyse the utilization of incinerated bio-medical waste ash (IBWA) combined with ground granulated blast furnace slag (GGBS) in reinforced GPC beams and columns. Medical waste was produced in the health-care industry, specifically in hospitals and diagnostic laboratories. GGBS is a form of industrial waste generated by steel factories. The best option to address global warming is to reduce the consumption of Portland cement production and promote other types of cement that were not a pollutant to the environment. Therefore, the replacement in ordinary Portland cement construction with GPC is a promising way of reducing carbon dioxide emissions. GPC was produced due to an alkali-activated polymeric reaction between alumina-silicate source materials and unreacted aggregates and other materials. Industrial pollutants such as fly ash and slag were used as raw materials.

Laboratory experiments were performed on three different proportions (reinforced cement concrete [RCC], 100% GGBS as an aluminosilicate source material in reinforced geopolymer concrete [GRGPC] and 30% replacement of IBWA as an aluminosilicate source material for GGBS in reinforced geopolymer concrete [IGRGPC]). The cubes and cylinders for these proportions were tested to find their compressive strength and split tensile strength. In addition, beams (deflection factor, ductility factor, flexural strength, degradation of stiffness and toughness index) and columns (load-carrying ability, stress-strain behaviour and load-deflection behaviours) of reinforced geopolymer concrete (RGPC) were studied.

As shown by the results, compared to Reinforced Cement Concrete (RCC) and 100% GGBS based Reinforced Geopolymer Concrete (GRGPC), 30% IBWA and 70% GGBS based Reinforced Geopolymer Concrete (IGRGPC) (30% IBWA–70% GGBS reinforced geo-polymer concrete) cubes, cylinders, beams and columns exhibit high compressive strength, tensile strength, flexural strength, load-carrying ability, ultimate strength, stiffness, ductility and deformation capacity.

All the results were based on the experiments done in this research. All the result values obtained in this research are higher than the theoretical values.