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This paper aims to explore the relationship of promoter ownership and board structure with firm performance for Indian companies.

Corporate governance structures of 391 Indian companies out of CRISIL NSE Index (CNX) 500 companies listed on national stock exchange (NSE) have been studied for their impact on performance of companies. Panel data regression methodology has been used on data for five financial years from 2010 to 2014 for the selected companies. Performance measures considered are market-based measure (Tobin’s Q) and accounting-based measure (return on assets [ROA]).

The empirical findings indicate that market-based measure (Tobin’s Q) is more impacted by corporate governance than accounting-based measure. There is significant positive association between promoter ownership and firm performance. It is also indicated that the relationship between promoter ownership and firm performance is different at different levels of promoter ownership. Board size is found to be positively related to ROA; however, board independence is not found to be related to any of the performance measures.

Limitations of the study are in terms of data methodology and possible omission of some variables. It is felt that endogeneity and reverse causality might be better addressed using simultaneous equation methodology.

The paper adds to the emerging body of literature on corporate governance performance relationship in Indian context using a reasonably wider and newer data set.

This paper aims to explore the relationship between board characteristics and firm performance for Indian companies.

Corporate governance structures of 391 Indian companies out of CNX 500 companies listed on National Stock Exchange have been studied for their impact on performance of companies. Panel data regression methodology has been used on data for five financial years from 2010 to 2014 for the selected companies. Performance measures considered are market-based measure (Tobin’s Q) and accounting-based measure (return on asset [ROA]).

The empirical findings indicate that the market-based measure (Tobin’s Q) is more impacted by corporate governance than the accounting-based measure (ROA). There is a significant positive association between board size and firm performance. Board independence is found significantly related to firm performance. Number of board meetings is found to be sending positive signal to the market creating firm value. Separation of chief executive officer and chairman of the board is found to be value-creating, and overburdened directors affect firm performance adversely.

Limitations of the study are in terms of methodology and possible omission of some variables. It is understood that the qualitative dynamics happening inside board meetings impact corporate performance. The strategic decision-making process adopted by the boards to fight competition or to increase market share is not easily available in public domain. The decision-making processes and monitoring for implementation of those decisions could impact corporate governance performance relationship. These parameters and their impact on corporate performance are not covered under the scope of the present study.

The paper adds to the emerging body of literature on corporate governance performance relationship in the Indian context by using a reasonably wider and newer data set.

The purpose of this paper is to explore the relationship of board characteristics and firm performance for Indian companies.

Corporate governance structures of 391 Indian companies out of CNX 500 companies listed on National Stock Exchange have been studied for their impact on performance of companies. Structural equation modeling methodology has been employed on data for five financial years from 2010 to 2014 for selected companies. Market-based measure (Tobin’s Q) and accounting-based measure (return on asset) have been employed for measuring firm performance.

Empirical findings indicate that there is significant positive association between board size and firm performance. Board independence is found significantly related to firm performance. Number of board meetings is found to be sending positive signal to the market creating firm value. Separation of CEO and chairman of the board is found to be value creating and overburdened directors affect firm performance adversely. Findings also suggest that the governance-performance relationship is also dependent upon the type of performance measures used in the study.

Limitations of this study are in terms of data methodology and possible omission of some variables. It is understood that the qualitative dynamics happening inside board meetings impact corporate performance. The strategic decisions-making process adopted by the boards to fight competition or to increase market share is not available in public domain easily. The decision-making processes and monitoring for implementation of these decisions could impact corporate governance-performance relationship. These parameters and their impact on corporate performance are not covered under the scope of the present study. However, the same could have thrown more light on governance-performance relationship.

The paper adds to the emerging body of literature on corporate governance-performance relationship in the Indian context using a reasonably wider and newer data set.

Use of fossil fuels in automotive sector is one of the primary causes of greenhouse emissions. The automotive engines need to perform at their best efficiency point to limit these emissions. Most of the quality indicators in this regard are based on near steady state global operational characteristics for engines without considering local performance. In the present study, extensive numerical simulations have been carried out covering a wide range of steady state and transient operating conditions to quantify interaction of turbocharger with engines through turbo lag phenomena which may cause increased emissions during the load change conditions. Furthermore possible innovations have been explored to minimize turbo lag phenomena. The paper aims to discuss these issues.

In this paper quality indicators have been developed to quantify the performance of turbocharged diesel engine under the transient event of rapid change in fueling rate which has been rarely investigated. The rate of fueling is changed from 40 mm3/injection to 52 mm3/injection at 1,000 rpm engine speed which corresponds to normal operating condition. To improve quality of transient response, torque assistance method and reduction of inertia of compressor wheel have been used. Parametric study has been undertaken to analyze the quality indicators such as outlet pressure of the compressor and the compressor speed. The turbo lag is quantified to obtain the close to optimal transient response of turbocharged diesel engine.

It has been shown that, with torque assist the transient response of the internal combustion engine is significantly improved. On the other hand, marginal improvement in transient response is observed by the reduction in inertia of the compressor wheel.

The findings indicate that turbo lag can be minimized by providing torque assistance by active and passive means.

The developed methods can be used in practice for efficient operation of vehicles.

The work carried out in the paper provides a way to minimize harmful emissions.

The quality indicators developed provide a quantitative measure of turbo lag phenomena and address the above mentioned problems.

Substantial pressure from civil society and investors has forced governments around the world to take climate neutrality initiatives. Several countries have pledged their nationally determined contributions towards net-zero. However, there exist various obstacles to achieving the same and the agriculture sector is one of them. Thus, this study identifies and models the critical barriers to achieving climate neutrality in the agriculture food supply chain (AFSC).

Sixteen barriers are identified through a literature survey and are validated by the questionnaire survey. Furthermore, the interactions amongst the barriers are estimated through the application of the “weighted influence non-linear gauge system (WINGS)” method which considers the both intensity of influence and the strength of the barrier. To mitigate these barriers, a framework based on green, resilient and inclusive development (GRID) is proposed.

The obtained results reveal that lack of collaboration amongst AFSC stakeholders, lack of information and education awareness, and lack of technical expertise obtained a higher rank (amongst the top five) in three indicators of the WINGS method and thus are the most significant barriers.

This paper is the first attempt in modelling the climate neutrality barriers for the Indian AFSC. Additionally, the mitigating strategies are prepared using the GRID framework.

Online customer communities have become a strategic tool for business-to-business (B2B) firms to drive collaboration among customers around the company’s products and services. This paper aims to argue that the three social capital dimensions, that is, structural, relational and cognitive, themselves driven by brand community trust, can affect brand loyalty for the organization.

The authors use a survey to collect data and structural equation modeling to test the conceptual framework by collecting data from 214 participants across three online B2B communities operated by three technology firms in India.

Brand community trust is found to have a strong association with social network ties, identification and norm of reciprocity and shared vision. These three have concomitant effects on the quality of customer-to-customer (C2C) interactions. Such communication generates functional, emotional and social benefits, which, in turn, curate brand loyalty.

The authors’ findings guide community managers in leveraging such conversations in shaping customer loyalty for the corporate brand.

This work provides an integrated framework to explain the important role of C2C interactions in B2B online brand communities.

Advertising clutter has fueled the rise of nontraditional advertising methods. The current study, conducted in India, adopted the consumer socialization framework to assess product placement attitudes and behaviors.

A questionnaire-based survey was conducted to gauge consumers' responses to product placements. Structural equation modeling (SEM) was applied to analyze the relationship between different variables.

The results revealed that young Indian adults are positive about product placements as they believe that incorporating brands into the content adds realism. The authors found that socialization agents significantly impact viewers' attitudes toward product placements which in turn influence their purchase intentions. The authors also found that product acceptability impacts consumers' purchase intentions.

This paper provides important insights into consumers' perceptions of product placements. Based on the findings, marketers can formulate effective product placement strategies.

Most of the studies existing in this area have been conducted in the developed markets except a few which have been conducted in the emerging markets. Hence, the present study is an attempt to fill this research gap. This study is among the first to establish a relationship between product acceptability and consumers' purchase intentions.

Increasing public consciousness and demand for sustainable environment make selection of a safe location for effective disposal of healthcare waste (HCW) a challenging issue. This problem becomes more complicated due to involvement of multiple decision makers having varying knowledge and interest, conflicting quantitative and qualitative evaluation criteria, and presence of several alternative locations.

To efficiently resolve the problem, the past researchers have already coupled different multi-criteria decision-making tools with uncertainty models and criteria weight measurement techniques, which are time-consuming and highly computationally complex. Based on involvement of a group of experts expressing their opinions with respect to relative importance of criteria and performance of alternative locations against each criterion, this paper proposes application of ordinal priority approach (OPA) integrated with grey numbers to solve an HCW disposal location selection problem.

The grey OPA can simultaneously estimate weights of the experts, criteria and locations relieving the decision makers from complicated computational steps. The potentiality of grey OPA in solving an HCW disposal location selection problem is demonstrated here using an illustrative example consisting of three experts, six criteria and four alternative locations.

The derived results show that it can be employed to deal with real-time HCW disposal location selection problems in uncertain environment providing acceptable and robust decisions. It relieves the experts from pair-wise comparisons of criteria, normalization of data, identification of ideal and anti-ideal solutions, aggregation of information and so on, while arriving at the most consistent decision with minimum computational effort.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.