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The purpose of this study is to examine the differential impact of qualitative and quantitative informational signals within the merger and acquisition (M&A) press releases on deal completion and duration. A significant percentage of deals by emerging market acquirers get abandoned before completion, and those that are completed have a longer duration. The limited information about the operations of acquirers from emerging markets creates suspicion among the stakeholders involved in deal resolution, hindering the completion of deals. Thus, using the signal-feedback paradigm, authors investigate how informational signals in the M&A press release impact the deal resolution.

The study employs content analysis on M&A press releases announced by firms from five emerging economies: Brazil, Russia, India, China and South Africa. The technique is applied based on the exploration-exploitation framework developed by March (1991) to categorize the announced deal motives (qualitative information). Next, the authors identify the percentage of relevant quantitative information disclosed in the press release, following which results are obtained using logistic and ordinary least square regressions.

The study reports that deals with declared exploratory motives take longer to complete. Additionally, deals disclosing higher percentage of quantitative disclosure exhibit lower completion rate and increased deal duration.

This is the first study to provide evidence that familiarity bias impacts deal duration as relative to exploitation deals that are familiar to the stakeholders; exploratory deals take longer to conclude. Further, our analysis indicates that a greater percentage of quantitative disclosure may not always reduce information risk but rather be interpreted negatively in the form of the acquirer’s overconfidence in the deal’s potential.

This paper aims to present an improvement to the power quality of the grid by using a colliding body optimization (CBO) based proportional-integral (PI) compensated design for a grid-connected solar photovoltaic-fed brushless DC motor (BLDC)-driven water pumping system with a bidirectional power flow control. The system with bidirectional power flow allows driving the pump at full proportions uninterruptedly irrespective of the weather conditions and feeding a grid when water pumping is not required.

Here, power quality issue is taken care of by the optimal generation of the duty cycle of the voltage source converter. The duty cycle is optimally generated by optimal selection of the gains of the current controller (i.e. PI), with the CBO technique resulting in a nearly unity power factor as well as lower total harmonic distortion (THD) of input current. In the CBO technique, the gains of the PI controller are considered as agents and collide with each other to obtain the best value. The system is simulated using MATLAB/Simulink and validated in real time with OPAL RT simulator, OP5700.

It was found that the power quality of grid using the CBO technique has improved much better than the particle swarm optimization and Zeigler–Nichols approach. The bidirectional flow of control of VSC allowed for optimum resource utilization and full capacity of water pumping whatever may be weather conditions.

Improved power quality of grid by optimally generation of the duty cycle for the proposed system. A unit vector tamplate generation technique is used for bidirectional power transfer.

This paper aims to assess the impact of corporate social irresponsibility (CSiR) media coverage on firm performance in India. It also analyses the effects of the environment, social, governance, and cross-cutting issues on firm performance.

The paper utilizes a sample of Indian firms from the Reprisk^® database, amounting to 1,103 CSiR media coverage counts for 693 firm-year annual observations from 2008 to 2015. Further, Reprisk^® segregates comprehensive CSiR coverage counts into the environment, social, governance and cross-cutting issues, for which the study runs the fixed effects panel regression. The study takes year-fixed effects, industry-fixed effects and clustered standard errors at the industry level.

The results of this study indicate that CSiR coverage negatively influences the firm performance of Indian firms. All issues, including social, governance and cross-cutting, except environmental issues, negatively impact firm value in India.

The involvement of firms in CSiR costs the firms financially and drives down firm performance. Social issues, including community and employee-related matters, governance issues and cross-cutting issues, also reduce the firm performance.

The insignificant environmental impact on firm performance does not indicate that environmental issues have no detrimental consequences. Instead, it might need more stakeholders' awareness to understand the harmful implications of environmental issues on society.

Limited studies have explored CSiR in India so far. The study is novel as it analyses the Reprisk^® database and its segregation of media counts into the environment, social, governance and cross-cutting issues in the Indian context.

The present research identifies a total of nine factors influencing tax avoidance under the international taxation regime of the developing countries and establishes a hierarchical relationship through modeling of the identified factors using modified-total interpretive structural modeling (M-TISM).

Due to “scale without mass” properties of the digital economy, businesses reduce their physical presence in the countries of economic activities. Aided with digital features, multinational enterprises (MNEs) avoid, abolish, or adopt flexible tax burden in the developing nations through by-passing the permanent establishment condition for company taxes or the income characterization prerequisite for royalty taxation. The present research endeavors to identify the drivers of tax avoidance in the developing countries, especially exacerbated due to digital technologies (economy). In addition, the authors also examine the hierarchical relation between the extracted drivers of tax avoidance.

This research presents a considerable driving force of elements like historical foundation of tax-treaties, dominance of the developed countries, influence of trade bodies in policy matters and finally information and communications technologies (ICTs).

Identified elements drive the actors like professional enablers, tax havens, international organizations, and intangible assets in the form of intellectual properties (IPs) which act upon tax arbitrage situations both under the domestic and treaty regulations, finally culminating into profit shifting, tax manipulations or avoidance.

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.

The purpose of this paper is to validate the theoretical finding that digital MNEs avoid physical presence norms of permanent establishment and royalty characterization rules for business and royalty taxation, respectively, to escape tax incidence in the market economy, using information, communication and technology features and transfer pricing (TP) manipulations.

Multiple case studies of MNEs from technology sector, based on judicial decisions in 141 cases, over taxability of profits earned from Indian economic activities. Additional in-depth case study of the Uber Group to study the tax avoidance structures under platform economy, by routing of Indian profits through The Netherlands, a tax haven.

The study finds a significant number of digital MNEs earning profits from India and avoiding tax by defying physical presence and royalty characterization. In majority of the cases, demand-side business activities are discharged through incorporating and remunerating affiliates at cost plus low markup, thus avoiding tax incidence, using TP manipulations under the arm’s length principle applied by governments for benchmarking the intragroup transactions of the MNEs.

The research findings validate the view that digital features promote tax avoidance in the market economy.

The originality of the study lies in the validation of profit shifting through digital features from the developing market economy and portending that digital MNEs defy physical presence to avoid business taxation through TP manipulations.

Investors who can transfer their savings to investments in a well-regulated market benefit not only themselves but also economic development. Hence, it is crucial for fund owners to evaluate their stock market investment decisions. The goal of the study is to understand which model determines the asset returns most efficiently. In this regard, the validity of single and multi-index asset pricing models (capital asset pricing model-CAPM and Fama–French models) has been examined in the Turkish Stock Exchange for 2009–2020, with the quantile regression (QR) approach.

On 18 portfolios comprised of quoted stocks in the Istanbul Stock Exchange 100 (ISE-100/BIST-100), we test the CAPM, the Fama and French three factor model (FF3) and the Fama and French five factor model (FF5). Empirical analyses have been carried out via QR approach regressing the portfolios' average weekly excess returns on risk premium/market factor (Rm-Rf), firm size, book value/market value (B/M), profitability and investments factors. QR estimation has been employed since QR is more effective and provides a better definition of the distribution’s tails.

Our empirical findings have revealed that the average excess weekly returns can be explained more strongly via CAPM. Moreover, Fama and French models are expected to give more reliable result with more data, whereas the market premium would give robust results for the Turkish Capital Market.

Individuals investing in financial assets must find the price model that best fits the market. The return can be approximated in the most appropriate manner using the right variables.

The study differs from other research by comparing the asset pricing models via examining the assets' weekly returns with QR in the Istanbul Stock Exchange 100 (ISE-100).

Today’s in-demand skills may not be needed tomorrow. As companies are adopting a new group of technologies, they are in huge need of information technology (IT) professionals who can fill various IT positions with a mixture of technical and problem-solving skills. This study aims to adopt a sematic analysis approach to explore how the US Information Systems (IS) programs meet the challenges of emerging IT topics.

This study considers the application of a hybrid semantic analysis approach to the analysis of IS higher education programs in the USA. It proposes a semantic analysis framework and a semantic analysis algorithm to analyze and evaluate the context of the IS programs. To be more specific, the study uses digital transformation as a case study to examine the readiness of the IS programs in the USA to meet the challenges of digital transformation. First, this study developed a knowledge pool of 15 principles and 98 keywords from an extensive literature review on digital transformation. Second, this study collects 4,093 IS courses from 315 IS programs in the USA and 493,216 scientific publication records from the Web of Science Core Collection.

Using the knowledge pool and two collected data sets, the semantic analysis algorithm was implemented to compute a semantic similarity score (DxScore) between an IS course’s context and digital transformation. To present the credibility of the research results of this paper, the state ranking using the similarity scores and the state employment ranking were compared. The research results can be used by IS educators in the future in the process of updating the IS curricula. Regarding IT professionals in the industry, the results can provide insights into the training of their current/future employees.

This study explores the status of the IS programs in the USA by proposing a semantic analysis framework, using digital transformation as a case study to illustrate the application of the proposed semantic analysis framework, and developing a knowledge pool, a corpus and a course information collection.

The study seeks to explore why despite growing concern for the environment, consumers’ intention to purchase organic foods remains relatively low. In addition, the study also seeks to investigate the role of perceived marketplace influence (PMI) and moral norms in organic food consumption.

Data collected from 330 young consumers chosen with non-probability sampling were analysed using structural equation modelling in Amos 22.0.

The results of the parallel mediation analysis confirmed that environmental concern influences purchase intention indirectly through attitude, subjective norms, perceived behavioural control and perceived marketplace influence. In addition, moral norms were found to moderate the effect of perceived behavioural control on purchase intention. Moreover, the results also indicated that the impact of environmental concern on consumers’ attitude toward organic foods was also moderated by moral norms. Further, the results of moderated mediation showed that the indirect effect of environmental concern on purchase intention (through attitude and perceived behavioural control) was moderated by moral norms.

The study contributes to the existing literature by investigating the inconsistency between environmental concern and purchase intention. In addition, the study also investigate role of perceived marketplace influence and moral norms in stimulating organic food consumption intentions.

The emergence of perceived marketplace influence as an important determinant of organic food consumption shows that every individual needs to realise the importance of their environment friendly actions to promote organic food consumption. In addition, the study also highlights the pivotal role of moral norms in the promotion of organic food consumption. Thus, markets, policy-makers, family, friends, society all should promote and inculcate the spirit of contributing in the cause of safeguarding the environment to the young children specially by promoting consumption of organic foods.

The study examines the role of perceived marketplace influence as predictor of purchase intention towards organic foods which is rarely explored specially in the domain of organic food consumption. In addition, the results also produced some novel insights into the moderating role of moral norms.

Despite the widespread prevalence of share pledging by Indian promoters, this area remains out of the researchers’ purview. This study aims to bridge this research gap by delineating the impact of promoter share pledging on future stock price crash risk and financial performance in India.

A sample of 257 companies listed on the Standard and Poor’s Bombay Stock Exchange 500 (S&P BSE 500) Index has been analysed using panel (fixed-effects) data regression methodology over 2011–2020. Further, alternative proxies for crash risk and financial performance are adopted to ensure that the study’s initial findings are robust. Finally, the instrumental variable with the two-stage least squares (IV-2SLS) method has also been employed to alleviate endogeneity concerns.

The results suggest a significantly positive relationship between promoter share pledging and future stock price crash risk in India. Conversely, this association is significantly negative for future financial performance. Moreover, the results hold, even after including alternative proxies of stock price crash risk and financial performance and addressing endogeneity concerns.

Owing to the sizeable equity shareholdings of the promoters, share pledging has remained a lucrative source of finance in India. Despite the popularity, the findings of this study question the relevance of share pledging by Indian promoters considering its impact on aggravating future stock price crash risk and deteriorating future financial performance.