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This study aims to identify the critical factors contributing to India-based non-governmental organizations (NGOs) capacity building and value creation for beneficiaries.

A total interpretive structural modeling technique has been used to develop a hierarchical model of critical factors and understand their direct and indirect interrelationships. The driving force and dependence force of these factors were determined by using cross-impact matrix multiplication applied to classification analysis.

This study identifies 12 critical factors influencing NGO capacity building in India’s intellectual disability sector across four dimensions. Internal organizational capabilities include infrastructure, staff qualifications, fundraising, vocational activities and technical resources. Second, coordination and stakeholder engagement highlight government and agency collaboration, dedicated board members and stakeholder involvement. Third, adaptability and responsiveness emphasize adjusting to external trends and seizing opportunities. Finally, impact and value creation emphasis on improving value for persons with disabilities (PWDs).

The findings of this study have practical implications for Indian NGOs working for PWDs. The study provides NGOs with a structural model for improving organizational capacity by identifying and categorizing critical factors into the strategic model.

There is a scarcity of literature on capacity building for disability-focused NGOs in India. This study seeks to identify critical factors and develop a hierarchical model of those factors to assist policymakers in India in building the capacity of NGOs.

This study aims to examine the impact of online travel reviews (OTR) on tourists’ intention to travel based on the stimulus–organism–response (SOR) model. Further, it explored the mediating effects of tourist trust in OTR.

In this direction, this study proposes and empirically validates a conceptual model after collecting data from 299 Indian consumers. Proposed hypotheses were tested by applying the structural equation modelling technique. Bootstrapping method was used for mediation testing.

The findings revealed that various attributes of OTR exert differential impacts on travel intention. The study also confirmed the mediating role of tourist trust in OTR.

This study offers significant practical implications for travel marketers. To capitalize on OTR, travel marketers are recommended to develop an effective and efficient online reviews management system. This will improve the quality, valence, quantity and consistency of OTR, which in turn will enhance tourist trust in OTR, leading to improved travel intention.

No empirical evidence has been traced on how OTR enhances tourist trust in OTR and their travel intention. In support of this, the present study proposes and empirically validates an extensive model to comprehend the role of various drivers of OTR in improving tourist trust in OTR, leading to enhanced travel intention based on the SOR model.

Most of the services being delivered to persons with disabilities (PwDs) in India are through non-government organizations (NGOs). The quality and effectiveness for the delivery of services to PwDs largely depends on the capacity of the NGOs involved. This study attempts to understand the linkage between various capabilities of non-profits organizations working in the field of intellectual and developmental disabilities and their value creation.

Using a mixed methodology, the study has conducted various interviews with the involved stakeholders and interviews to obtain a complete understanding and overcome the limitations of quantitative or qualitative approach alone.

The findings of this study exhibit that there is a significant and positive influence of financial capability, human resource capability, stakeholder capability, dynamic capability and collaboration capability on non-profit performance. However, knowledge capability has no effect on non-profit performance.

This study will help in making policies for policymakers in capacity building of NGOs. This research study is the first attempt in exploring the critical factors in capacity building of NGOs in the intellectual disability sector, particularly in India.

The study examines the influence of a firm's life cycle on the cash flow classification of Indian firms.

The study employs Dickinson's (2011) cash flow patterns to classify firm years under various life-cycle stages. Cash flow classification is employed to measure a firm's classification shifting (CS) practices. The study includes Indian firms listed on the Bombay Stock Exchange during 2012–2020, an ordinary least squares regression model, a fixed-effect model and a panel corrected with standard error regression method.

Firms face different opportunities and challenges at different stages of the firm's life cycle and therefore adopt cash flow CS. The results show that firms adopt cash flow CS during introduction, growth and decline stage of life cycle either to boost or to reduce operating cash flows.

This study is one of its kind to study the influence of a firm's life cycle on the cash flow classification of Indian firms.

Enrolling in an academic discipline or selecting the college major choice is a dynamic process. Very few studies examine this aspect in India. This paper makes a humble attempt to fill this gap using NSSO 71st round data on social consumption on education. The purpose of this paper is to use multinomial regression model to study the different factors that influence course choice in higher education. The different factors (given the availability of information) considered relate to ability, gender, cost of higher education, socio-economic and geographical location. The results indicate that gender polarization is apparent between humanities and engineering. The predicated probabilities bring out the dichotomy between the choice of courses and levels of living expressed through consumption expenditures in terms of professional and non-professional courses. Predicted probabilities of course choices bring in a clear distinction between south and west regions preferring engineering and other professional courses, whereas north, east and NES prefer humanities.

The present paper follows the same approach as that of Turner and Bowen (1999). The Multinomial regression is specified as P ( M i = j ) = ( exp ( β j × X i ) / ∑ j − 1 5 exp ( β j × X i ) ) , where P (M_i=j) denotes the probability of choosing outcome j, the particular course/major choice that categorizes different disciplines. This response variable is specified with five categories: such as medicine, engineering, other professional courses, science and humanities. The authors’ primary interest is to determine the factors governing an individual’s decision to choose a particular subject field as compared to humanities. In other words, to make the system identifiable in the MLR, humanities is treated as a reference category. The vector X_i includes the set of explanatory variables and β_j refers to the corresponding coefficients for each of the outcome j. From an aggregate perspective, the distribution of course choices is an important input to the skill (technical skills) composition of future workforce. In that sense, except humanities, the rest of the courses are technical-intensive courses; hence, humanities is treated as a reference category.

The results indicate that gender polarization is apparent between humanities and engineering. The predicated probabilities bring out the dichotomy between the choice of courses and levels of living expressed through consumption expenditures in terms of professional and non-professional courses. Predicted probabilities of course choices bring in a clear distinction between south and west regions preferring engineering and other professional courses, whereas north, east and NES prefer humanities.

Predicted probabilities of course choices bring in a clear distinction between south and west regions preferring engineering and other professional courses, whereas north, east and NES prefer humanities. This course and regional imbalance need to be worked with multi-pronged strategies of providing both access to education and employment opportunities in other states. But the predicted probabilities of medicine and science remain similar across the board. Very few research studies on the determinants of field choice in higher education prevail in India. Research studies on returns to education by field or course choices hardly exist in India. These evidences are particularly important to know which course choices can support student loans, which can be the future area of work.

The research evidence is particularly important to know which course choices can support student loans, which can be the future area of work, as well as how to address the gender bias in the course choices.

The paper has social implications in terms of giving insights into the course choices of students. These findings bring in implications for practice in their ability to predict the demand for course choices and their share of demand, not only in the labor market but also across regions. India has 36 states/UTs and each state/UT has a huge population size and large geographical areas. The choice of course has state-specific influence because of nature of state economy, society, culture and inherent education systems. Further, within the states, rural and urban variation has also a serious influence on the choice of courses.

The present study is a value addition on three counts. First, the choice of courses includes the recent trends in the preference over market-oriented/technical courses such as medicine, engineering and other professional courses (chartered accountancy and similar courses, courses from Industrial Training Institute, recognized vocational training institute, etc.). The choice of market-oriented courses has been examined in relation to the choice of conventional subjects. Second, the socio-economic background of students plays a significant role in the choice of courses. Third, the present paper uses the latest data on Social Consumption on Education.

1. To understand the importance of creating and implementing a vision for enhancing gender diversity and inclusion relevant to the manufacturing and engineering sector in an emerging market.

2. To develop insights into the vision and characteristics of an inclusive leader.

3. To evaluate the strategies and organizational levers that created and nurtured a climate of gender diversity and inclusion in Cummins India.

4. To identify organizational levers that will enable the sustenance and institutionalization of a climate of inclusion.

This case study traces a 16-year journey of diversity and inclusion at Cummins India, a subsidiary of the Fortune 500 manufacturing organization Cummins Inc. headquartered in the US. Initially spearheaded by Anant Talaulicar, and then continued by Ashwath Ram, gender D&I initiative at Cummins India has made significant strides. Talaulicar had an opportunity to immerse himself in the ethos of the parent company before joining the Indian subsidiary.

In India during the early 2000s the external environment was characterized by rapid technological and regulatory changes and increasing complexity. To make matters more difficult, the internal culture was steeped in a traditional manufacturing mindset marked by dismal female participation rate and an over-representation of locals with similar beliefs and value systems.

Given the mammoth task already taken up by Talaulicar by improving the diversity numbers from 3% to 33%, Ram had big shoes to fill. On one hand, he had to drive the business amidst uncertain market conditions; on the other hand, he had to carry on a legacy. Given that he himself had a lived experience of Cummins global values, he knew D&I was an integral part of the Cummins way of life. His familiarity with the socio-cultural challenges of the country coupled with his drive to continue and rejuvenate the D&I agenda, brought some interesting, yet challenging, questions for him. With the internal and external pressures looming large before him, could he institutionalize a climate of inclusion that could serve as a strategic lever to place the company on the path of growth, vibrancy and economic prosperity?

Through qualitative research conducted by the authors, this case study brought out learnings pertaining to linkage of leadership in creating a climate of inclusion and expansion of talent diversity through a set of people strategies and HR practices. The contribution of this case study is primarily to theory and practice in the field of Human Resource Management, D&I as well as in developing inclusive leadership.

MBA programs and leadership development programs

Teaching notes are available for educators only.

CSS 6: Human Resource Management.

This paper aims to conduct, a detailed investigation of various Reynolds averaged Navier–Stokes (RANS) models to study their performance in attached and separated flows. The turbulent flow over two airfoils, namely, National Advisory Committee for Aeronautics (NACA)-0012 and National Aeronautics and Space Administration (NASA) MS(1)-0317 with a static stall setup at a Reynolds number of 6 million, is chosen to investigate these models. The pre-stall and post-stall regions, which are in the range of angles of attack 0°–20°, are simulated.

RANS turbulence models with the Boussinesq approximation are the most commonly used cost-effective models for engineering flows. Four RANS models are considered to predict the static stall of two airfoils: Spalart–Allmaras (SA), Menter’s k – ω shear stress transport (SST), k – kL and SA-Bas Cakmakcioglu modified (BCM) transition model. All the simulations are performed on an in-house unstructured-grid compressible flow solver.

All the turbulence models considered predicted the lift and drag coefficients in good agreement with experimental data for both airfoils in the attached pre-stall region. For the NACA-0012 airfoil, all models except the SA-BCM over-predicted the stall angle by 2°, whereas SA-BCM failed to predict stall. For the NASA MS(1)-0317 airfoil, all models predicted the lift and drag coefficients accurately for attached flow. But the first three models showed even further delayed stall, whereas SA-BCM again did not predict stall.

The numerical results at high Re obtained from this work, especially that of the NASA MS(1)-0317, are new to the literature in the knowledge of the authors. This paper highlights the inability of RANS models to predict the stall phenomenon and suggests a need for improvement in modeling flow physics in near- and post-stall flows.

Innovation is a prerequisite for economic and technological growth of any organization. Identifying enablers of innovation can help managers accelerate the process of economic growth. The purpose of this paper is to identify the prominent enablers of innovation in small and medium enterprises (SMEs) that can help overhauling organizations and benefit them economically.

A comprehensive literature review and expert’s opinions have been applied to identify enablers of innovation. A case of automotive component supplier is considered for conducting the research. A coalescence of Grey and DEMATEL methodologies has been incorporated to first rank the enablers of innovation based on their importance and then identify the causal relationship among these enablers by characterizing enablers into causal and effect groups.

A few important enablers, namely, entrepreneur traits, knowledge management, resources for innovation, and linkage capabilities, have been identified as prominent enablers for successful innovation in SMEs.

This paper identifies enablers of innovation in SMEs and the causal relationship between these enablers. The identified enablers and the causal relationship between these enablers will help managers of small organizations in selecting the enablers that need to be focused on, which, in turn, can drive other enablers of innovation, thus saving time and resources of the organizations.

This paper uses a novel Grey–DEMATEL methodology to identify the causal relationship among enablers and also contributes to the literature on innovation by identifying enablers of innovation in SMEs.

The study proposes to determine the impending challenges to lean integration with Industry 4.0 (I4.0) in manufacturing that aims at achieving desired operational performance. Integrating lean and Industry 4.0 as the two industrial approaches is synergetic in providing operational benefits such as increasing flexibility, improving productivity, reducing cost, reducing delivery time, improving quality and value stream mapping (VSM). There is an urgent need to understand the integrated potential of OPEX strategies like lean manufacturing and also to determine the challenges for manufacturing SMEs and further suggest a strategic roadmap for the future.

The current work has used a combined approach on interpretative structural modeling (ISM) and fuzzy Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) approach to structure the multiple level analysis for the implementation challenges to integrate OPEX strategies with Industry 4.0.

The research has found that the indulgence of various implementation issues like lack of standardization, lack of vision and lack of trained support, all are the major challenges that inhibit the integration of OPEX strategies with I4.0 technologies in manufacturing.

The research has investigated the internal factors acting as a roadblock to lean and Industry 4.0 adoption. Further studies may consider external factors to lean and Industry 4.0 implementation. Also, further research may consider other operational excellence approaches and extend further to relevant sectors.

This study provides the analysis of barriers that is useful for the managers to take strategic actions for implementing OPEX strategies with I4.0 in smart manufacturing.

The research determines the adoption challenges towards the integrated framework. This is the first study to explore challenges in integrating OPEX strategies with I4.0 technologies in manufacturing SMEs.

This case brings out the role of institutions and corporate governance issues in regulatory/policy organisations in the telecom sector. Spectrum is a critical input for mobile services, the economic growth driver. The Indian government, like other governments, attempted to move to a more flexible spectrum governance regime and introduced trading to ensure that more spectrum became available for commercial services. Despite its efforts, the government's framework was restrictive. The spectrum trading deal between the two private telecom operators-RCom and Reliance Jio-failed. RCom was fighting to remain solvent by selling spectrum, and Reliance Jio needed it for its growth.