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This study aims to describe the fundamentals of teaching risk management in a classroom setting, with an emphasis on the learning interface between higher education and the workplace environment for business management students.

The study reviews literature that uses spreadsheets to visualize and model risk and uncertainty. Using six distinct case-based activities (CBAs), the study illustrates the practical applications of software like Palisade @RISK in risk management education. It helps to close the gap between theory and practice. The software assists in estimating the likelihood of a risk event and the impact or repercussions it will have if it occurs. This technique of risk analysis makes it possible to identify the risks that need the most active control.

@RISK can be used to create models that produce results to demonstrate every potential scenario outcome. When faced with a choice or analysis that involves uncertainty, @RISK can be utilized to enhance the perspective of what the future might contain.

The insights from this study can be used to develop critical thinking, independent thinking, problem-solving and other important skills in learners. Further, educators can apply Bloom’s taxonomy and the problem-solving taxonomy to help students make informed decisions in risky situations.

The purpose of this paper is to empirically investigate linkage among productivity, quality, and business performance in home-based brassware units in India.

This study involved action research of home-based brassware units applying procedures for three-stage least-squares (3SLS) regression analysis, with data obtained through questionnaire survey based on convenience sampling.

This study has supported the established belief that quality leads to productivity, and subsequently productivity leads to better business performance for home-based brassware units in India. The consistent and logical result of this study using 3SLS regression analysis has provided empirical understanding of the appropriate linkage among productivity, quality, and business performance.

This study has limitations of findings, as it studied the home-based brassware units in the Indian context only.

This study implies that marketable home-based brassware products are to be produced by taking into account boundaries of production within the framework of goals and value created by motivation and dependability for monitoring the business performance. Identifying an appropriate linkage among productivity, quality, and business performance may project a holistic evaluation of the policy development related to home-based brassware units.

This is an original study to test empirical linkages among productivity, quality, and business performance using 3SLS regression analysis particularly for home-based brassware units in India.

The purpose of this paper is to develop and explain an empirically validated scale to measure service quality for architects in India.

This study applies a systematic procedure for development of a psychometric scale in three phases. Phase 1 includes item generation and selection through review of literature and expert opinion. Phase 2 comprises scale refinement using item analysis and exploratory factor analysis. Phase 3 applies confirmatory factor analysis (CFA) for establishing convergent, discriminant and nomological validity. This study has involved 15 expert participants in Phase 1 and sought participation from 250 respondents using an online questionnaire in two other independent phases.

The findings of the empirical study resulted in the development of a 22-item scale that measures the constructs such as design quality, project administration quality, communication quality, relationship quality and dependability quality.

This study has developed a context-specific psychometric scale of service quality for architects in India using snowball sampling. Although this study identified five valid service quality factors, the classified information relating to the formation of expectations was not collected.

This reliable and valid scale would be helpful for architects to measure the level of service quality in enhancing business performance. This study has established that service quality for architects is achieved only when the perceived benefits are available from the aspects like design, project administration, communication, relationship and dependability.

This study can facilitate an architect interested in opportunities relating to contracting, consulting and engineering to explore possibilities of higher fees from clients.

This study is an original attempt in developing a validated tool to measure service quality of architects in India.

The purpose of this paper is to outline the generic concepts and learning about smart cities and capture the varied perspectives of winning case examples in India. An attempt is made in the paper to study the available literature about smart cities and structure them into a synoptic framework of planning, design and implementation.

This paper has followed a case study approach and complied multi-facet 18 features of 99 winners of “100 Smart Cities Mission” in India to showcase trends and developments of tomorrow. These multi-facet features collectively provide a heterogeneous view of the future potentials of smart cities in India.

Findings of this research can contribute to shaping a number significant learning of different aspects of policy formation in India with respect to smart cities in view of the sensitivity of citizen participation in the individualized society of information age.

The results and learning of this study have not been verified empirically through a survey and they are based on qualitative incidences in the submitted proposal. Further, the state of this paper is generic and there is a lack of city-specific context specification except for some illustrations of success stories and upcoming innovative projects.

This paper provides a better understanding of current practices fulfilling featured requirements of smart cities to identify opportunities for improvement based on the current state of the debate.

The development of smart cities in India is expected to play an outstanding role in shaping the world of tomorrow. Although the focus of this development is on the actual needs and requirements of today; however, some trends and predictions of the future society can also be identified.

This paper is the original attempt to set the definition of developing and replicating smart cities in India based on decisive parameters and it contributes to meet challenges of urban planning.

The purpose of this paper is to develop a model for generic competencies based on lifecycle orientation of projects to support infrastructure managers (IMs) in India.

This study has reviewed literature on competency theories and their advancement of knowledge in management, construction and engineering projects. This study has applied exploratory factor analysis (EFA) to structure generic competencies founded on infrastructure practices in India. Further this study has applied confirmatory factor analysis (CFA) to test for confirmation on emerged dimensionality of the competence construct for IMs in India.

Using data collected from 175 usable questionnaires of managers serving in infrastructure firms in India for EFA followed by CFA, six generic competencies have been established in the domains of strategic, analytical, personal, managerial, professional and leadership dimensions significantly impacting competent performance.

This study has applied plausibility sampling and it presents only generic competencies for executives working in the infrastructure sector alone.

Due to the growth in number of executives to be employed in infrastructure firms in India, academic institutions in this subcontinent have gained momentum in offering programmes covering the field of infrastructure management. These institutions are believed to be covering domains of strategic, analytical, personal, managerial, professional and leadership dimensions for assuring competent performance of IMs in India.

Attention to these generic competencies can help IMs to contribute towards better performance, academic institutions to design curriculum, recruiters to acquire talent and executives to advance professionally.

Extant academic studies relating to generic competencies are available mostly in project and construction domains. There is a paucity of such academic studies in the domain of infrastructure.

Implementing enterprise risk management (ERM) systems in construction firms of developing countries like India is critical for targeting strong risk management strategies that support their growth. It requires such firms to holistically understand the major barriers in terms of their definitions, relationships with one another and interdependencies. Thus, this study aims to identify, model and analyze the barriers to implementing ERM in construction firms using interpretive structural modeling (ISM).

This study used a Delphi process to identify barriers to the implementation of ERM in Indian construction firms, ISM to model them and Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) to analyze their interrelationships.

The study’s results revealed that individual-level factors are the most important among the barriers present at the lowest level in the hierarchical model, whereas organizational commitment with the highest dependence power is present at the highest level in the hierarchical model.

Since the usage of ERM in the construction industry is highly culture-dependent and may have regional nuances, the data on ERM usage might accurately reflect the Indian construction industry but may not apply to other regions.

This study can be used to develop effective strategies to improve the implementation of ERM in construction firms in developing countries like India.

ERM is crucial for managing risks in Indian construction firms due to the high degree of complexity and uncertainty associated with construction projects coming from changes due to technological advancement, regulatory changes, changes in consumer preferences, global competition and other socioeconomic and political factors.

The study’s results will help researchers and practitioners working in the construction industry of developing countries like India to identify the challenges in adopting ERM systems. It will guide construction firms to appropriately develop risk management strategies for managing the inevitable risks in their complex project environments. This will help improve their contribution to the country’s economic development.

The purpose of this paper is to propose a low carbon culture (LCC) adoption model for gaining the right carbon capabilities by integrating the dimensions of flexibility or control and external or internal of competing values framework (CVF) with that of level of carbon emission (LCE).

This study reviewed literature related to low carbon supply chain, CVF and carbon capabilities to synthesize currently available frameworks for assessing culture and carbon-related insights. Based on these insights, this study proposes the carbon culture adoption model and presents some research propositions.

This study has extended categorization of culture suggested in CVF from four categories to eight distinct categories by adding “LCE” as a third dimension. The new categories of carbon culture are: “Red,” “Antagonist,” “Obligatory,” “Early Adopter,” “Follower,” “Transitive,” “Pragmatist” and “Green.” This categorization of organizations would help in selecting appropriate low carbon practices (LCPs).

This study presents purely conceptual framework with some research propositions which needs to be empirically tested.

Organizations can formulate right policies for low carbon capabilities based on the LCC of their supply chain.

With increasing awareness about environment across stakeholders, organizations around the world are under pressure to reduce their carbon footprints. The extent of reduction in carbon footprints depends on the right capabilities across the supply chain which in turn depends on selection of the right combination of LCPs based on the supply chain culture.

Automakers are engaged in manufacturing both efficient and inefficient green cars. The purpose of this paper is to categorize efficient green cars and inefficient green cars followed by improving efficiencies of identified inefficient green cars for distribution fitting.

The authors have used 2014 edition of secondary data published by the Automotive Research Centre of the Automobile Club of Southern California. The paper provides the methodology of applying data envelopment analysis (DEA) consisting of 50 decision-making units (DMUs) of green cars with six input indices (emission, braking, ride quality, acceleration, turning circle, and luggage capacity) and two output indices (miles per gallon and torque) integrated with Monte Carlo simulation for drawing significant statistical inferences graphically.

The findings of this study showed that there are 27 efficient and 23 inefficient DMUs along with improvement matrix. Additionally, the study highlighted the best distribution fitting of improved efficient green cars for respective indices.

This study suffers from limitations associated with 2014 edition of secondary data used in this research.

This study may be useful for motorists with efficient listing of green cars, whereas automakers can be benefitted with distribution fitting of improved efficient green cars using Monte Carlo simulation for calibration.

The paper uses DEA to empirically examine classification of green cars and applies Monte Carlo simulation for distribution fitting to improved efficient green cars to decide appropriate range of their attributes for calibration.

This study aims to examine whether or not residential properties closer to landfill sites have lower offer values by the developers. That is, by analyzing real estate data and landfill site locations, the study seeks to provide insights into whether properties situated closer to landfill sites tend to have a lower offer values than those located farther away.

The study is exploratory in nature, and a case study approach is applied. A landfill site named “Uruli Devachi” is selected in the region of Pune district, and data is collected from 102 developers selling residential projects within a radius of 15 km (about 9.32 mi). The gathered data is analyzed by using basic descriptive statistics, one-way ANOVA and ordinary least squares (OLS) regression. The OLS regression helps to determine whether there is a relationship between the distance of a residential property from a landfill site and its offer value.

The findings suggest that landfill sites have a detrimental impact on residential property offer values, with the negative impact increasing with proximity to a landfill site. The negative effect seems to vanish after over 10 km (about 6.21 mi). The developers provide extra facilities including a clubhouse, a children’s play area, a gym and a swimming pool in an effort to mitigate the negative effects of the landfill site on residential properties.

The findings of this study could have implications for property developers, real estate professionals and policymakers in understanding how landfill proximity might impact property offer values.

This study presents many novelties for the Indian housing market: the landfill sites do have a negative effect on the offer value of residential property; the closer the residential property to a landfill site, the higher the negative effect. Further, the developers try and mitigate the negative effect of landfill sites on residential properties by providing additional amenities such as a clubhouse, children’s play park, gym and swimming pool.

The purpose of the study is to examine the value-based performance of firms in construction sector in India using Tobin's Q and Market Capitalization (MCAP) and then determine their significant financial drivers.

The study is based on data from 87 firms engaged in infrastructure, real estate, industrial construction and allied areas in India over a study period of 10 years. Three distinct forms of panel regression models have been developed using Tobin's Q and MCAP as dependent variables. The models developed are using Baltagi's (1981) Error Component 2SLS, Varadharajan-Krishnakumar's (1987) Generalized 2SLS and Arellano – Bower/Blundell – Bond's (1991) dynamic panel.

The study found that MCAP is a better suited value-based performance measure for construction sector firms in India. The study further reports that the age of the firm, profit after tax, investment in research and development, dividends, leverage and net fixed asset are significant positive drivers, whereas cash flow is a significant negative driver.

The study is limited to a geographic location; therefore, the findings of this study cannot be generalized.

As MCAP is a better suited value-based performance measure of a firm in the construction sector, managers should focus on improving profitability, higher research and development activities, higher dividends and higher expenditures on net fixed assets for improvement.

This is an original attempt to examine the value-based performance of firms in the construction sector in India using Tobin's Q and MCAP.