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Market efficiency suggests that price of the security must reflect its intrinsic value by impounding all the available and accessible information. Asset pricing in capital markets has been an exceptionally dynamic area of scholarly research and is considered as a barometer for assessing market efficiency. This phenomenon was very well explained by several market pricing models and theories over the last few decades. However, several anomalies, which cannot be explained by the traditional asset pricing models due to seasonal and psychological factors, were observed historically. The same has been studied by several researchers over the years and is well captured in the literature pertaining to market asset pricing. The purpose of this paper is to revisit the research studies related to a few asset pricing anomalies, collectively referred to as “calendar anomalies”, such as – day-of-the-week, turn-of-the-month, turn-of-the-year and the holiday effects. In this pursuit, a thorough survey of literature in this area, published over the last 80 years (from 1934 to 2016) across 24 prominent journals, has been made and presented in a comprehensive, structured and chronologically arranged major findings and learnings. This literature survey reveals that the existing literature do provide a great depth of understanding around these calendar anomalies often with reference to specific markets, the size of the firm and investor type. The paper also highlights a few aspects where the existing literature is silent or provides little support leaving a gap that needs to be addressed with further research in this area.

The goal of the study requires a comprehensive review of the past literature related to calendar anomalies. As a consequence, to identify papers which sufficiently represent the area of study, the authors examined the full text of articles within EBSCOHost, Elsevier-Science direct, Emerald insight and JSTOR databases with calendar anomalies related keywords for articles published since inception. Further, each article was classified based on the anomaly discussed and the factors used to sub-categorize the anomaly. Once all the identified fields were populated, we passed through another article by constantly updating the master list till all the 99 articles were populated.

It is also important to understand at this juncture that most of the papers surveyed discuss the persistence of the asset pricing anomalies with reference to the developed markets with a very few offering evidences from emerging markets. Thus leaving a huge scope for further research to study the persistence of asset pricing anomalies, the degree and direction of the effect on asset pricing among emerging markets such as India, Russia, Brazil vis-a-vis the developed markets. Further, regardless of the markets with reference to which the study is conducted, the research so far appears to have laid focus only on the overall market returns derived from aggregate market indices to explain the asset pricing anomalies. Thus leaving enough scope for further research to study and understand the persistence of these anomalies with reference to various strategic, thematic and sectoral indices in various markets (developed, emerging and underdeveloped countries) across different time periods. It will be also interesting to understand how, some or all of, these established asset pricing anomalies behave over a certain time period when markets move across the efficiency maturity model (from weak form to semi-strong to strong form of efficiency).

The main purpose of the study entails a detailed review of all the past literature pertinent to the calendar anomalies. In order to explore the prior literature that sufficiently captures the research area, various renowned databases were examined with keywords related to the calendar anomalies under scope of current study. Furthermore, based on the finalized articles, a comprehensive summary table was populated and provided in the Appendix which gives a snapshot of all the articles under the current assessment. This helps the readers of the article to directly relate the findings of each article with its background information.

Spunlacing is a promising nonwoven technology for the production of fabric with good handle and better structural integrity. Structural parameters such as pore size, thickness and number of binding point/entanglement between fibres are decisive for good mechanical and comfort properties of nonwoven fabrics. This study aims to focus on the effect of different process parameters on the structural change in spunlace fabrics.

Spunlacing is purely a mechanical bonding technology where high-speed jets of water strike a web to entangle the fibres. Different spunlace nonwoven structures were produced by varying processing parameters such as waterjet pressure, delivery speed, web mass and web composition as per four-factor, three-level Box–Behnken design. The effect of these parameters on the structural arrangement was studied using scanning electron microscopy. An attempt has also been made to study the changes in pore geometry and thickness of the fabrics by using response surface methodology with backward elimination.

Significant structural changes were observed with variation in water pressure, web mass and web composition. The test results showed that fabric produced at higher waterjet pressure has lower mean pore diameter and lower thickness. The variation in mean pore diameter and mean thickness due to waterjet pressure is around 26 and 34 per cent, respectively, at 95 per cent significance level. The web composition and web mass also significantly influence the mean pore diameter and thickness at 95 per cent significance level. There is a strong positive correlation (r = 0.523) between mean air permeability and mean pore diameter of fabric, and this correlation is significantly linear. A strong negative correlation (r = −0.627) is found between weight and air permeability of fabric.

The delivery speed failed to show any significant effect; this is in contrary to the general expectation.

The effect of concurrent variation in waterjet pressure, web mass, delivery speed and web composition on the structure of spunlace nonwoven is studied, which was not reported in the literature. The effect of web composition on pore diameter of spunlace nonwoven is interesting finding. This study is expected to help in designing the spunlace nonwoven as per end uses and specifically for apparel application.

Asset pricing revolves around the core aspects of risk and expected return. The main objective of the study is to test different asset pricing models for the Indian securities market. This paper aims to analyse whether leverage and liquidity augmented five-factor model performs better than Capital Asset Pricing Model (CAPM), Fama and French three-factor model, leverage augmented four-factor model and liquidity augmented four-factor model.

The data for the current study comprises records on prices of securities that are part of the Nifty 500 index for a time frame of 14 years, that is, from October 2004 to September 2017 consisting of 183 companies using time series regression.

The results indicate that the five-factor model performs better than CAPM and the three-factor model. The model outperforms leverage augmented and liquidity augmented four-factor models. The empirical evidence shows that the five-factor model has the highest explanatory power among the entire asset pricing models considered.

The present study bears certain useful implications for various stakeholders including fund managers, investors and academicians.

This study presents a five-factor model containing two additional factors, that is, leverage and liquidity risk along with the Fama-French three-factor model. These factors are expected to give more value to the model in comparison to the Fama-French three-factor model.

This study empirically examines the relationship between the effective bid‐ask spread on foreign currency options traded on the Philadelphia Stock Exchange and the likelihood of a transaction occurring. Important contributions of this research include the use of a more precise measure of the effective bid‐ask spread than generally used in the literature and the use of data on actual transactions, plus several requests for quotes that did not culminate in a transaction. Consistent with prior theoretical work in the market micro structure literature, the results document empirical evidence that the likelihood of a transaction is inversely proportional to the effective bid‐ask spread.

The present study aims at developing a model to quantify supply chain resilience as a single numerical value. The numerical value is called resilience index that measures the resilience capability of the case company's supply chain. The model calculates the index value based on the interactions between the enablers of supply chain resilience and its dimensions.

Graph theoretic approach (GTA) is used to evaluate the resilience index for the case company's supply chain. In GTA, the dimensions of resilience enablers and their interdependencies are modelled through a digraph. The digraph depicting the influence of each dimension is converted into an adjacency matrix. The permanent function value of the adjacency matrix is called the resilience index (RI).

The proposed approach has been illustrated in context of an Indian automobile organization, and value of the RI is evaluated. The best case and the worst-case values are also obtained with the help of GTA. It is noted from the model that strategic level dimension of enablers is most important in contributing towards supply chain resilience. They are followed by tactical and operational level enablers. The GTA framework proposed will help supply chain practitioners to evaluate and benchmark the supply chain resilience of their respective organizations with the best in the industry.

A firm can compare the RI of its own supply chain with other's supply chain or with the best in the industry for benchmarking purpose. Benchmarking of resilience will help organizations in developing strategies to compete in dynamic market scenario.

This paper is an empirical study of outsourcing practices in the banking sector in India. The purpose of the paper is to investigate the impact of factors which influence the decision makers' attitude towards outsourcing.

Based on a review of the existing literature, an attitudinal model of outsourcing was developed. This model was used to: identify the key factors of benefits, risks, roadblocks, and criticality of outsourcing; develop the instrument to measure the factors; and formulate hypotheses concerning the impact of these factors. The constructs in the instrument that measured these factors were validated by factor analysis.

The impacts of perceived benefits, perceived roadblocks, and perceived criticality on the attitudes towards outsourcing were found to be strong and statistically significant. The impact of perceived risk was weak and statistically insignificant. The model explaining the combined impact of these four factors on outsourcing attitudes was also statistically significant.

An important insight from this study is that the clients, at least in the banking sector in India, tend to value in outsourcing quality factors such as process improvement, services improvement and cost transparency more than cost savings. The results of the study provide a basis for rethinking the value proposition offered by outsourcing vendors and for refocusing the research on outsourcing of services in particular.

While most studies on outsourcing tend to be theoretical and/or focus on outsourcing from developed to developing countries, this is an empirical study focusing on outsourcing by organizations based in developing countries such as India. Therefore, the results are not confounded by differences in culture‐specific communications, business practices, and regulatory regimes between the countries.

This paper aims to study the concept, characteristics and factors of the resilient supply chain (RSC) and develop a hierarchical structural model and classify the factors based on their interrelationships.

This paper has used a mixed-approach of literature review and expert opinion to identify the factors of RSC. For the development of the structural model and clustering of the factors, this paper has used the total interpretive structural modeling approach with Matrice d’Impacts Croises-Multiplication Applique and Classment and decision-making trial and evaluation laboratory analysis.

In total, this study has identified 17 factors that enable the 3R capability of the RSC. The result shows that the factors have a close dependence relationship with supply chain (SC) risk management culture as the most influencing factor. Further, this study classifies the factors into enablers and strategies.

This research work is the theoretical contribution to the RSC concept and helps the experts to develop and improve the resilient ability in the SC. This research is based entirely on subjective expert feedback; thus, the results are sensitive to the expert’s judgment.

This research will help the decision-makers in allocating the resources and policies to develop or improve the SC capabilities.

This research work is the first kind of research in the field of the RSC that considers the 3R concept to identify and model the resilient factors of the SC. Along with the theoretical concept, this research provides empirical evidence for the importance ranking of the factors.

The enormous amount of waste generated and the scarcity of natural resources worldwide have encouraged societies and industries to adopt the Circular Supply Chain (CSC) concept. With a focus on zero-waste generation, Circular Economy (CE) mimics the ecosystem cycle as an alternative to the traditional linear economic model. This paper aims to investigate the evolution of research themes in this research area, hence, trace the trajectory of development in the field of CSC.

The authors conduct scientometric analysis using Pajek and VOSviewer software to identify key themes in the Circular Supply Chain Management (CSCM) field. The Citation Path Analysis (CPA), including Main Path and Local Path analysis, has been followed by a critical review of the papers. This paper includes highlighting the interrelationships between the information flows in the topic of study as well as an analysis of keywords co-occurrence.

The analysis of keywords co-occurrence revealed that the earlier years of research in CSC were more inclined toward value chain, stakeholders and green supply chains, whereas, in recent years, topics like logistics, Industry 4.0 and food supply chain have been more focused upon. Further, the Main Path Analysis (MPA) revealed an evolving trajectory that examines challenges and opportunities in CSC, the economic aspects of implementing CSC, the impact on the firm's revenue growth and collaboration between multiple echelons of a supply chain and Industry 4.0.

The adoption of scientometrics analysis unveils the hidden flow of information, various themes of research and their interconnections. The development of research trajectories and progressive attention paid to certain topics is also discovered. The research findings could be used by researchers for further theoretical and research development.

This paper traces the path of development in the field of CSC and its emerging trends and provides a thorough understanding of the same. It enables research scholars to conduct an in-depth study in the CSC domain, adding to the body of literature.

We investigate institutional investors’ trading behavior of acquiring firm stocks surrounding merger activities for the period 1992–2001. We label investment companies and independent investment advisors as active institutions and banks, nonbank trusts, and insurance companies as passive institutions. We analyze the trading behavior of active and passive institutions surrounding merger announcements and their eventual resolution. Our results indicate that active institutions significantly increase their holdings of acquiring firm stocks for mergers with higher announcement period abnormal return and this increase is more pronounced for stock mergers than cash mergers. Active institutions display preference for stock proposals at the merger announcement on the basis of their prior beliefs and this is explained by the “overreaction phenomenon.” However, they update their beliefs between announcement and final resolution as more information arrives into the market. Finally, active institutions appear to correct their overreaction behavior by displaying their greater preference for cash proposals as compared to stock proposals at the quarter of eventual outcome. The trading behavior of passive institutions suggests that these institutions disregard the market response of merger announcement in trading acquiring firm stocks at the announcement quarter. The passive institutions gradually update their beliefs and utilize the information released at the announcement in rebalancing their portfolios at the final resolution.