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The purpose of this paper is to identify and rank critical factors influencing investment decisions of venture capitalists.

To identify and prioritize factors affecting investment decisions of venture capitalists, a two-phase methodology was adopted: in the first phase, critical factors influencing venture capitalists’ investment decisions were identified using exploratory factor analysis; the second phase entailed the use of a multi-criteria decision-making technique – analytical hierarchal process (AHP) which involved assigning weights to, and prioritizing the identified criteria and sub-criteria.

Seven factors were found to significantly influence investment decisions of venture capitalists: entrepreneur’s characteristics, product or services, market characteristics, management skills, financial consideration, economic environment and institutional and regulatory environment. Findings revealed that entrepreneur’s characteristics, financial consideration and product or services were prime influencers of venture capitalists’ investment decisions.

As for limitations, first, the study considers limited number of factors influencing investment decisions of venture capitalists; there may be other influencers not considered in this study. Second, the AHP methodology assumes that the various decision-making criteria and sub-criteria are independent of each other; in real life, there may be inter-dependency among criteria. Third, the hierarchal model has been tested in the Indian venture capital industry only, and generalizability of results with respect to other industries is questionable.

The present study identifies and ranks seven factors found to significantly influence investment decisions of venture capitalists. Venture capitalists could use this list of factors as a guideline before making investment decisions, and if considering all factors is not possible, take into account the factors given top rank so that they arrive at informed and intelligent decisions.

This study is the first to identify economic factors (economic environment and institutional & regulatory environment) as influencers of venture capitalists’ investment decisions. Further, no study in the past has attempted to rank or prioritize factors influencing venture capitalists’ investment decisions; this is the first attempt of the kind.

The purpose of this paper is to identify key determinants of foreign direct investment (FDI) inflows in developing countries by using unbalanced panel data set pertaining to the years 1990-2012. This study considers 20 developing countries from the whole of South, East and South-East Asia.

Using seven explanatory variables (market size, trade openness, infrastructure, inflation, interest rate, research and development and human capital), the authors have tried to find the best fit model from the two models considered (fixed effect model and random effect model) with the help of Hausman test.

Fixed effect estimation indicates that market size, trade openness, interest rate and human capital yield significant coefficients in relation to FDI inflow for the panel of developing countries under study. The findings reveal that market size is the most significant determinant of FDI inflow.

Like any other study, this work also has some limitations. Lack of data on key determinants such as labor cost, exchange rate, corruption, natural resources, effectiveness of rule of law and political risk may be considered one such limitation. Further, controlling for variables such as exchange rate, corruption, labor cost and political risk could make significant improvements to this study.

This study has significant implications for policy makers, mangers and investors. Policy makers would be able to understand the importance of the major determinants of FDI mentioned in the paper, and take steps to formulate policies that encourage FDI. Such measures could include developing market size, making regulations more international trade friendly and investing in the nation’s human capital. Further, steps could be taken to keep interest rates and inflation rates under control as these factors have been found to influence FDI.

The sample of 20 developing nations chosen for this study has not been considered by any study earlier. This is a unique contribution to existing body of research, and highlights the originality value of this paper.

The consumption of supplementary cementitious materials (SCMs) has increased enormously in the construction industry. These SCMs are often waste materials or industrial by-products. This study aims to investigate the bond strength using reinforcing bars in Normal Strength Concrete (M20 grade) and High Strength Concrete (M40 grade), developed using SCMs and data was compared with concrete prepared with ordinary portland cement (OPC). The findings of the study will help in reducing the dependency on OPC and promote the utilization of waste materials in Construction.

In the present study, the bond behavior between the steel bars and the concrete was investigated in controlled, binary and quaternary concretes of M20 and M40 grades. Following the conventional procedures, samples were prepared and mechanical tests conducted (as per IS:2770–1 code for M20 and M40 grade concrete structures), which showed an improvement in the bond strength depending on the extent of overall calcium and silica content in these composite mixtures, and thus reflected the importance of vigilant utilization of used industrial waste in the OPC as a replacement without exceeding silica content beyond certain percentages for enhanced structural properties.

Experimental evaluation of bond behavior results showed a brittle nature for the controlled (OPC) concrete mixtures. While binary and quaternary concrete was able to resist the load-carrying capacity under large deformations and prevented the split cracking and disintegration of the concretes. Among different variations in the chemistry, for both M20 and M40 grades, the maximum bond strengths were observed for 10% Metakaolin + 10% Silica Fume + 30% Fly Ash + 50% OPC composition and this could be attributed to the fineness of the additives, better packing and enhanced calcium silicate hydrate (C-S-H).

Quaternary concrete may be a future option in place of OPC concrete. Very limited data is available related to the bond strength of quaternary concrete. Experimental analysis on quaternary concrete shows that its use in construction can reduce both construction cost and a burden on natural raw materials used to make OPC.

This study examined Indian institutional investors' holding data to understand their investment strategy (Portfolio Concentration/Diversification) and explored whether their skills were associated with their portfolio strategy and performance. The study introduced a new proxy to identify skilled investors by forecasting abnormal returns. Moreover, the study also highlighted where skilled Indian investors put their money for long-term investment.

This study measures portfolio concentration based on the number of holdings, the Hirschman–Herfindahl index (HHI) and benchmarks adjusted industry concentration. The study introduced a new proxy to identify skilled investors. We measured Investors' performance with the help of Carhart's four factors model and examined the relationship between variables through various regression models.

The study concluded a negative relationship between portfolio concentration and performance. However, skilled Indian investors get rewards from portfolio concentration decisions. It was found that skilled investors with few stocks and an industry concentration in their portfolio show a positive association between concentration and fund performance. Additionally, this study found Indian investors showing their faith in the financial sector for long-term investment.

This study examined Indian institutional investors' portfolio concentration strategy and introduced a new proxy to measure investors' skills.

This paper aims to examine the hedge, diversifier and safe haven properties of the global listed infrastructure sector and subsector indices against two traditional asset classes, stocks and bonds, and four alternative asset classes, including commodities, real estate, private equity and hedge funds during extreme negative stock market movements.

Using dynamic conditional correlation and quantile regression, the authors analyze a data set of 12 indices comprising listed infrastructure and traditional asset classes from 2010 to 2019.

Overall, the findings indicate that listed infrastructure acts as an effective diversifier but not as a strong safe haven or hedge when considered in a multiasset context. With minor exceptions, listed infrastructure cannot be concluded as a safe haven against other asset classes under investigation.

The present study has implications for institutional investors looking to incorporate infrastructure in their multiasset portfolios for increased portfolio diversification benefits.

Despite the increased influence of infrastructure as an asset class, to the best of the authors’ knowledge, this is the first study to investigate the hedge, safe haven and diversifying properties of infrastructure in a multi-asset context.

The mounting focus on environmental, social and governance (ESG) factors in business has sparked substantial curiosity in understanding the nexus between ESG and the companies’ strategic decisions. This study aims to investigate the influence of firms’ ESG disclosure scores on their dividend payout. Furthermore, it examines the nuanced dynamics of this relationship by exploring the moderating role of the country’s investor protection regulations and regulatory enforcement.

This study uses pooled ordinary least square regression with year, industry and country effects. It analyzes a balanced panel data set of 192 non-financial firms drawn from the primary equity indices of BRICS nations. This study examined the data of six years spanning 2015–2020.

The findings discover a significantly positive relationship between ESG scores and dividend payout ratio, conveying that firms with higher ESG scores allocate more of their profits as dividends. Furthermore, the finding reveals that country-level robust investor protection and effective regulatory enforcement mechanisms undermine the positive association between ESG ratings and payouts of dividends, suggesting that the ESG disclosure of firms operating in a setting characterized by enhanced investor safeguards and stricter regulatory oversight will exert less influence on their dividend decisions.

To the best of the authors’ knowledge, this is the first study to concentrate on the ESG–dividend nexus in the BRICS countries. Furthermore, this study used each country’s investor protection index and regulatory enforcement scores to comprehend the influence of country-level legal frameworks in shaping the relationship between ESG and dividend decisions, thus adding value to the existing literature on corporate sustainability.

One of the most contested and anticipated research issues is the acceptability of using recycled aggregates instead of fresh aggregates. This study aims to look at the possibility of replacing fresh aggregates with 15%, 30%, 60% and 100% recycled aggregates.

The research is divided into two stages. The compressive, split tensile, flexural and bond strength of the various mixes were examined in the first phase using untreated recycled concrete aggregates (RCA). The second phase entails chemically treating RCA with a 10% 0.1 M sodium metasilicate solution to evaluate differences in strength, indicating the success of the treatment performed. Microstructural experiments such as scanning electron microscopy and X-ray diffraction were also conducted to evaluate the formation of interfacial transition zone (ITZ) in treated and untreated RCA specimens.

The observed findings reveal a decrease in concrete strength with increasing RCA concentration; however, when treated RCA was used, the strengths increased significantly when compared to untreated samples. The findings also include curves indicating the correlation between compressive strength and other mechanical strength parameters for an optimum mix of concrete prepared with 30% RCA replacement.

The study through its novel approach, demonstrates the effect of pretreatment of RCA in the absence of any standardized chemical treatment methodology and presents significant potential in minimizing reliance on fresh aggregates used in concrete, lowering building costs and promoting the use of waste materials in construction.

The purpose of this paper is to combine the critical parameters used to study financial inclusion into a composite index. The idea is to rank Indian states and union territories (UTs) on the basis of this index, determine change in ranks during 2011 to 2014 and identify factors affecting high/low scores on the index.

Data for the study were collected from secondary sources published by Reserve Bank of India (RBI) and Central Statistical Organization. Applying technique of order preference by similarity to ideal solution (TOPSIS), a composite multi-dimensional index of financial inclusion (IFI) has been built by using three broad parameters of penetration, availability and usage of banking services. Factors significantly influencing scores of states/UTs on IFI were identified using multiple regression analysis.

The value of financial inclusion for India on composite IFI has increased by 0.045 points during the study period. Share of agriculture to state gross domestic product, literacy ratio, population density, infrastructure development and farmer suicides are significant factors affecting financial inclusion.

The multi-dimensional IFI is a useful tool to measure financial inclusion using several parameters for various states/regions. The index can also be used to compare the performance of states/regions over same/different periods.

This paper is unique in its attempt to construct multi-dimensional IFI for Indian states/UTs by applying TOPSIS. It will prove useful for future researchers by combining several aspects of financial inclusion into single index.

Driving cycle is an essential requirement to evaluate the exhaust emissions of various types of vehicles on the chassis dynamometer test. This study presents a real world comparison of the driving cycles of Edinburgh motorcycles in two world cities; Edinburgh in Scotland and Delhi in India. The two driving cycles (EMDC & DMDC) driving cycle (EMDC) that were was developed through the analysis of experimental data. This data was collected from trips on a number of routes in each city. In Edinburgh, five different routes between the home addresses in the surrounding areas and place of work at Edinburgh Napier University in Edinburgh were selected. In Delhi data were collected in East Delhi (Geeta Calony) to Central Delhi (Raisena Road). The data collected data was divided into two categories of urban and rural roads in the case of Edinburgh while it was only the urban route in Delhi.. Forty four trips were made on the five designated routes in both urban and rural areas and 12 trips were made in Delhi. The aims of the study were to assess the various parameters (i.e. motorcycle speed, cruise, accelerations and decelerations and percentage time spent in idling) and their statistical validity over total trip lengths for producing a real world EMDC in each of the two cities. The results show that EMDC in Edinburgh, the EMDC has a cycle length of 770 and 656 seconds for urban and rural trips, respectively, which was found more than ECE cycle length. Time spent in acceleration and deceleration modes were found to be significantly higher than any other driving cycle reported to date for motorcycles, reflecting a typical characteristic of the driving cycle in Edinburgh; this was presumably due to diverse driving conditions of motorcycles in the city. In Delhi on the other hand, the DMDC has a cycle length of 847.5 seconds for the urban trips, which higher than that of the EMDC length. The overall percentage time spent in acceleration in Delhi was higher than that of Edinburgh while the time spent in deceleration was lower in Delhi. The overall average speed in the case of Delhi was slightly higher than that of Edinburgh.

The purpose of this paper is to discuss a comprehensive literature survey of studies focusing on the efficiency and productivity of the banking sector using parametric and non‐parametric frontier techniques.

Critically reviewing 106 studies published across the world from 1994 to 2011, a conceptual framework is developed for the studies assessing the efficiency and productivity of the banking industry using non‐parametric DEA frontier approach.

Both the frontier approaches, parametric and non‐parametric, are gaining an edge over the traditional financial performance measures. In the non‐parametric approach, data envelopment analysis (DEA) is widely applied to measure a bank's efficiency and productivity. Studies conducted in developed countries such as the USA, the UK and Europe are now emerging with the new concepts of banking efficiency.

These findings are based only on the critical review of 106 studies. This study suggests the direction for future research and identifies the gap in existing literature with the development of a conceptual model.

This study is original in nature and included literature published in recent issues of 2011.