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This paper aims to examine the destabilization effect in the case of India’s agricultural commodity market for the sample period of 01 January 2009 to 31 May 2013.

The daily data of eight agricultural commodities traded on the National Commodity & Derivatives Exchange, viz., barley, castor seed, chana (chickpea), chilli, potato, pepper, refined soya and soybean, have been used in this study. At the first stage of the empirical analysis, the study estimates the time-varying spot market volatility by using the exponential generalized autoregressive conditional heteroscedasticity model and applies three different high and band-pass filters, viz., the two-sided linear band-pass filter by Hodrick and Prescott (1997), the fixed-length symmetric band-pass filter by Baxter and King (1999) and the asymmetric band-pass filter by Christiano and Fitzgerald (2003), to calculate the unexpected liquidity of sample commodities. At the second stage of the empirical analysis, the study applies linear Granger causality and recently developed non-linear causality given by Diks and Panchenko (2006) to examine the cause and effect between time-varying volatility of spot market and futures market liquidity of sample commodities.

The linear and non-linear causality results suggest the destabilizing effect of commodity futures on the underlying spot market for chana, chilli and pepper. The empirical findings are in contrast with the recommendations of Abhijit Sen’s committee and provide important direction for further policy research.

The study has a limitation in that it is based on the daily data. The use of intra-day data would have been more suitable for such type of analysis.

The study has strong policy implications from a financial policy perspective, as there is already disagreement among researchers and policy makers with regard to the functioning of commodity derivatives markets in India. There have been many occasions when commodity market regulators have to undertake decisions of suspension of trading of many commodities. The study also provides new directions of policy research with regards to the restructuring of the commodity derivatives market in India.

The findings of this study may further help the regulators and policy makers to undertake decisions about how to provide an alternative platform for farmers to sell their agricultural produce more efficiently. This will certainly have some impact on the socioeconomic set-up of the country, as India is primarily an agriculture-dominated country.

So far not many studies have investigated the destabilization hypothesis in the case of emerging markets. This study is a novel attempt to fill the gap. In the case of emerging markets and especially in the case of India’s commodity derivatives market, this is the first study that examines the destabilization hypothesis in the case of India by applying new methods of high and band-pass filters and non-linear causality.

The aim of this paper is to conduct a real time evaluation of polypyrrole as an anti‐corrosive pigment in epoxy polyamide coating.

This study deals with synthesis of polypyrrole (PPy) by chemical oxidative polymerisation in laboratory conditions. The synthesised PPy was characterised by employing FT‐IR, XRD, SEM and EDX analysis. Epoxy film of bisphenol type hardened with polyamide based curing agent was used as the binder. PPy was used as anti‐corrosive pigment in concentrations varying from 0 to 5 wt% in the coating. In addition to anti‐corrosive property, mechanical, chemical and weathering properties of the coating containing PPy were studied and compared with epoxy polyamide coating without PPy.

The result obtained through various tests showed that the coating with 1 and 2% PPy exhibited excellent weathering resistance, mechanical properties and improved chemical resistance.

The anti‐corrosion property of the coating can be tested by means of atmospheric exposure such as Florida test or by means of electrochemical impedance spectroscopy.

The results find application in anti‐corrosive paints for industrial application.

This research paper presents the results of anti‐corrosion behaviour of PPy in epoxy‐polyamide coating. Based on this result, a highly effective anti‐corrosive coating can be formulated by addition of small percentage of PPy in combination with other conventional pigments, thereby enhancing corrosion protection.

Previous research indicates that the goals consumers have when shopping influence their attention to and processing of information they encounter. The purpose of this paper is to study the effects of consumers' pre‐purchase goals on their responses to price promotions.

In three experiments, the existence of consumer goals (i.e. with or without a pre‐purchase goal) were manipulated and promotion characteristics including message framing, promotion format, and promotion depth were systematically varied to examine how consumers respond to these price promotions.

Consumers with a pre‐purchase goal were found to be more attracted to the promotion than those without a goal. More importantly, pre‐purchase goals interact with promotion characteristics and produce differential effects on willingness to buy. Consumers with a pre‐purchase goal are more attracted to promotions emphasizing reduced losses while those without a goal responded more favorably toward promotions emphasizing gains. Moreover, consumers with and without a pre‐purchase goal respond differently to various discount levels.

Existing research on price promotions has not examined the influence of consumers' pre‐purchase goals. This paper brings a new dimension to price promotion research. Understanding these variations in pre‐purchase goals across consumers will help sellers design more effective promotion programs

The purpose of this paper is to promote communication by using music, and through mutual understanding and culture exchange to establish world peace.

The research explains why music promotes world peace and gives examples through empirical research and statistics.

Music (those genres with harmonious melodies, with peaceful purposes and without religious, political objectives) can break down the borders of nation states and bind humanity together. Quoting J.J. Keki’s words: “Peace will begin with simple people.” “We should use whatever we have to create peace. If you think you have the body, use the body to bring peace; if you have music, use your music.” Music contains huge potential of contribution to peacebuilding, such as removal of direct and indirect violence, igniting hope and will of life and help integrating peacefully among communities.

Peacebuilding should not remain as a theoretical idea, as it is argued that it is useful to implement within daily life. Music is a language of communication which can remove hostility. While potentially a good tool for constructing harmony, music can, however, also result in deleterious effects, if it is misused.

This paper aims to synthesise block copolymers (PPy-b-ENP) of pyrrole (Py) and ethoxylated nonyl phenols (ENP) via redox systems in presence of ceric ammonium nitrate (CAN) at room temperature. The initiating radical was formed on reducing organic compound which in turn initiated polymerisation to give diblock copolymers containing chain ends of ENPs and polypyrrole (Ppy). The effects of the concentration of Ce⁺⁴ salt, ENPs and Py on both the yield and electrical conductivities of corresponding polymers were studied.

In total, 0.1 M stock solution of CAN:100 ml 1 M HNO₃ was prepared freshly (7 ml HNO₃ dissolved in 100 ml water) and used in 50 ml of 0.1 M CAN solution (2.7438 g CAN dissolved in 50 ml nitric acid solution). The reducing compound (Py) was dissolved in water. Py and ENP were added slowly to the flask with vigorous stirring. The content of the flask was flushed with oxygen-free nitrogen. The resulting copolymers were characterised with spectroscopic methods like Fourier transform infrared spectroscopy and scanning electron microscope.

In this study, DMSO-slightly soluble Py copolymers were produced with ENPs. The conductivities of copolymers were found to be in the range of 10-1 to 10-4 S/cm. Soluble and processable conductive polymers were developed.

In this study, the water solubility of ENPs diminishes the conductivity of copolymer because of its surfactant structure. When the CAN/Py ratio was increased, PPys and copolymers with both higher yield and lower conductivity values were obtained. The results indicated that solubilities and the yield of the polymers synthesised in the presence of ENP have increased considerably. ENP caused degradative chain transfer reaction to become significant compared with bimolecular termination, so the yield decreased with increasing ENP concentration about 20 g/l. Results showed that yield of the copolymers strongly depends on Ce⁺⁴ concentrations while of copolymers were measured to be 10-3 S/cm.

PPy-b-ENP diblock copolymers were prepared with Ce⁺⁴ as an oxidation agent in a single step.

These slightly soluble and conductive copolymers may overcome difficulties in the applications of PPy homopolymers and open new application areas.

PPy-b-ENPs of lightly soluble (in DMSO) and conductive (10-2 S/cm) copolymers have been synthesised in one step. The results indicate that the surface of the copolymer is composed of well-distributed nanospheres with an average particle diameter of 35-400 nm.

Reference price is a key input in deciding product/service prices by organizations and has a significant influence on consumer purchase decisions. This study aims to provide a deeper understanding of reference pricing literature using bibliometric analysis and offers specific research questions for future research in this domain.

Using a sample of 309 articles published between 1977 and 2021, the study conducts bibliographic coupling, citation analysis, cluster analysis, content analysis, keyword analysis and a three-field plot to map the intellectual structure of reference price.

The content analysis gave seven research clusters: (1) modeling reference price, (2) consumer perceptions of price (un)fairness, (3) price framing, (4) comparative price-based promotion, (5) reference price formulation, (6) pay-what-you-want (PWYW) pricing and (7) range theory and price perceptions. The study also delineates reference price literature across several parameters like authorship, highest cited paper, most popular journal, institutions, region-wise publication trend and author-networks. The emerging research themes for future scholars working in this domain have also been highlighted.

This is the first comprehensive study to explore reference price from a bibliometric lens. The study highlights and discusses the recent themes on reference price, from both academic and managerial perspectives.

This research explores the application of machine learning to optimize pricing strategies in the aftermarket sector, particularly focusing on parts with no assigned values and the detection of outliers. The study emphasizes the need to incorporate technical features to improve pricing accuracy and decision-making.

The methodology involves data collection from web scraping and backend sources, followed by data preprocessing, feature engineering and model selection to capture the technical attributes of parts. A Random Forest Regressor model is chosen and trained to predict prices, achieving a 76.14% accuracy rate.

The model demonstrates accurate price prediction for parts with no assigned values while remaining within an acceptable price range. Additionally, outliers representing extreme pricing scenarios are successfully identified and predicted within the acceptable range.

This research bridges the gap between industry practice and academic research by demonstrating the effectiveness of machine learning for aftermarket pricing optimization. It offers an approach to address the challenges of pricing parts without assigned values and identifying outliers, potentially leading to increased revenue, sharper pricing tactics and a competitive advantage for aftermarket companies.

Artificial intelligence–enabled voice assistants (VAs), such as Amazon's Alexa, Google Assistant, and Apple's Siri, are available in smartphones, smart speakers, and other digital devices and channels. Use of these VAs is growing rapidly and are expected to significantly impact purchase intentions. This article focuses on how the communications enabled and provided by these VAs influence VA evaluations and usage intentions, contingent on the stage of the customer journey.

This paper builds from work on VAs, work on artificial intelligence (AI) and work on communications, to offer a comprehensive and up-to-date understanding of how VA evaluations and usage intentions may be impacted by the communications from VAs, contingent on the stage of the customer journey.

This paper proposes a model for VA enabled communications impact VA evaluations. It builds from work on VAs, AI, communications, and customer journey management. In the proposed model, VA evaluations are not only impacted by source, message and recipient characteristics (per prior communication models), but also by (1) VA/AI specific features, like perceptions of humanness and perceptions of artificiality, and (2) stage of the customer journey.

This paper provides guidance to firms, as regards how VA communications may influence VA evaluations and usage intentions. As an initial conjecture, (1) increasing perceptions of humanness, (2) decreasing perceptions of artificiality (3) a better fit between communications style (e.g. abstract vs concrete), and request type (e.g. transactional vs informational) (4) a better fit between VA communications (e.g. information vs banter), and consumer perceptions of the VA (servant vs partner) and (5) a better fit between VA communications and the stage of the customer journey may positively influence VA evaluations and VA usage intentions.

This paper provides a fresh look at the impact of VA communications, clarifying how such communications impact VA evaluations and usage intentions at various stages of the customer journey.

The objective of writing this case study is to allow management students to engage with the complexities of mergers and acquisitions (M&As) in the insurance sector in an emerging economy like India. Upon completion of this case study, the students will be able to critically evaluate the business environment of the insurance sector of a developing economy like India, analyse the impact of M&As on the insurance industry of India, appraise the post-merger consequences and strategies to deal with these consequences, assess the applicability of market power and growth theories in the context of M&As and develop a strategic action plan for handling post-merger challenges.

On 3 September 2021, the Insurance Regulatory and Development Authority of India (IRDAI) approved the “Scheme” related to the merger of the non-life insurance division of Bharti AXA General Insurance Company Limited (“Bharti AXA”) with ICICI Lombard General Insurance Company Limited (“ICICI Lombard”). Earlier, on 21 August 2020, the boards of the companies had approved entering into definitive agreements through a scheme of arrangement. The merger received approvals from different regulatory bodies as mandated (Gandhi et al., 2023). Bhargav Dasgupta, managing director and Chief Executive Officer of ICICI Lombard, stated, “This is a landmark step in the journey of ICICI Lombard, and we are confident that this transaction would be value accretive for our shareholders” (FE Bureau, 2020). However, the merger posed a dilemma for Dasgupta and the management regarding crop insurance owing to its impact on profitability. Crop insurance historically had high claim ratios nearing 135% for ICICI Lombard for financial year 2018. The company ceased to underwrite this product from 2019 onwards (TNN, 2019). However, ICICI Lombard had to fulfil the three-year commitment made by Bharti AXA to the state governments of Maharashtra and Karnataka towards crop insurance. It was a scheme initiated by the Government of India, covering farmers against losses due to cyclonic rains, rainfall deficits and other unforeseen calamities. Dasgupta faced a challenge in managing the interests of the farmers and the company’s shareholders while balancing profitability, which had already been impacted by the COVID-19 pandemic. This case study delves into post-merger complexities in the financial sector non-life insurance industry in emerging countries like India.

This case study is suitable for undergraduate and post-graduate management students and executives from the insurance industry.

Teaching notes are available for educators only.

CSS 11: Strategy.

Significant advances have been made in the field of healthcare service delivery across the world; however, health coverage particular for the poor and disadvantaged still remains a distant dream in developing world. In large developing countries like India, disparities in access to healthcare are pervasive. Despite recent progress in ensuring improved access to health care in past decade or so, disparities across gender, geography and socioeconomic status continue to persist. Fragmented and scattered health records and lack of integration are some of the primary causes leading to uneven healthcare service delivery. The devised framework is intended to address these challenges. The paper aims to discuss these issues.

In view of such challenges, in this research a Big Data and blockchain anchored integrative healthcare framework is proposed focusing upon providing timely and appropriate healthcare services to every citizen of the country. The framework uses unique identification number (UID) system as formalized and implemented by the Government of India for identification of the patients, their specific case histories and so forth.

The key characteristic of our proposed framework is that it provides easy access to secure, immutable and comprehensive medical records of patients across all treatment centers within the country. The model also ensures security and privacy of the medical records based upon the incorporation of biometric authentication by the patients for access of their records to healthcare providers.

A key component of our evolved framework is the Big Data analytics-based framework that seeks to provide structured health data to concerned stakeholders in healthcare services. The model entails all pertinent stakeholders starting from patients to healthcare service providers.