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This study aims to explore the influence of corporate sustainability on organizational value, specifically focusing on companies ranked in the Just Capital Market ranking. The aim is to establish whether higher sustainability rankings are associated with increased firm value and to investigate how corporate social responsibility (CSR) activities affect both financial and non-financial outcomes.

This study uses the Ohlson model to assess the value-generation potential of the top and bottom ten companies in the Just Capital Market ranking from 2013 to 2018. The analysis involves evaluating stock prices and other financial metrics and incorporating non-financial indicators related to CSR activities to gain a comprehensive understanding of their impact on firm valuation.

The results indicate a strong connection between high sustainability rankings and increased market value. Companies such as Microsoft, Intel and Alphabet, which have robust CSR initiatives, have shown significant improvements in market performance due to greater stakeholder engagement and detailed non-financial disclosures. On the other hand, companies with low sustainability ratings have demonstrated weaker market performance, which indicates the financial risks associated with neglecting CSR activities. This study underscores the critical importance of integrating CSR into fundamental business strategies to create sustainable value.

This study addresses the limitations of traditional financial indicators by incorporating non-financial factors into the valuation process. The study offers a more comprehensive assessment of firm value, reflecting modern business practices and the evolving global economy landscape. Integrating nonfinancial indicators enhances valuation accuracy and provides a holistic view of company performance, enabling stakeholders to make informed decisions based on a broader range of factors. This innovative method may reshape firm valuations, leading to more accurate and reliable assessments in contemporary business contexts.

The article investigates the wealth generation from takeover bids through an event study, analyzing the impact of announcements on stock returns of target and bidder firms across the industries and related and unrelated industry acquisitions. It aims to provide insights into financial implications for shareholders and market participants, contributing to understanding merger dynamics and informing investment decisions.

The methodology involves data collection of announcement dates, defining event and estimation windows. Market models and four-factor models are applied to compute abnormal returns. Linear regression estimates return, which is aggregated and tested for significance, providing insights into the wealth effects of takeover announcements.

Analysis reveals positive returns for both firms' shareholders on the announcement day, particularly significant for target firms. Pre-announcement, positive abnormal returns suggest potential information leakage, but reverse post announcement. Comparative model analysis emphasizes the role of systematic risk. Notably, a prolonged bidding process benefits the target firm. Trading in target company stocks under unrelated industry acquisitions appears to be more beneficial during the bidding.

This article introduces a novel approach by utilizing a four-factor model for computing abnormal returns, unlike previous research relying solely on the market model. It also focuses separately on related and unrelated industry acquisitions. This methodology captures comprehensive systematic risk, resulting in more conservative and robust abnormal returns. This methodological advancement addresses existing gaps in the literature and provides actionable insights for stakeholders in mergers and acquisitions.

This study aims to assess the impact of information and communication technologies (ICT) and financial inclusion on economic growth. This study also examines whether ICT can be a determinant of financial inclusion. Moreover, this study provides new evidence concerning whether ICT can reduce the financial inclusion gap.

This study uses the country-level data over the period 2005–2019 and estimate using the dynamic and the static panel model.

The results show that the ICT and financial inclusion interaction variable substantially and positively impacts economic growth for only certain interaction variables. ICT is an essential determinant of financial inclusion and reduces some gaps.

This study contributes to the literature by considering whether ICT and financial inclusion impact economic growth in high- and low-income countries. The other contribution of this study is that ICT represents a determinant in promoting financial inclusion. The final contribution of this study is providing new evidence concerning whether ICT can reduce the financial inclusion gap so that financial access can increase, financial inclusion can develop and simultaneously encourage economic growth.

The following are the objectives of the case study: building and leveraging core competence, realizing the strategic advantage of incumbency and contribution to nation building as a business potential.

Larsen and Toubro (L&T) started as a trading company in 1938. By 2023 L&T was a mammoth infrastructure company with a market cap INR 4,750bn operating 800–1,000 projects in engineering and construction at any point in time. It also worked in the domain of hydrocarbons, power and heavy engineering including defence engineering, financial services and development projects supported by technology. The company went through several phases of environmental disruptions in the form of the Second World War and India’s independence, which brought several opportunities for growth. L&T built competencies to leverage these opportunities, which also contributed to the nation building efforts in India. In 2023, several changes were occurring in the ecosystem in the form of energy changes, sustainability becoming a way of life and digitalization impacting every aspect of business. The managing director and chief executive officer Mr S.N. Subrahmanyan reiterated the need to focus on performance to make L&T a global leader in futuristic tech-driven engineering and solutions. He faced three major challenges – reducing exposure in non-core businesses, adopting technology to strengthen traditional business and leveraging the competence built over 85 years to improve the performance of L&T, while contributing to nation building.

This case study is suitable for MBA and executive programmes.

Teaching notes are available for educators only. Video of protagonist in conversation with Anant Maheshwari, President Microsoft India discussing the future plans of L&T for adopting new age technology. The video is available at the following YouTube link https://www.youtube.com/watch?v=OKb-_z_ch4E

CSS 11: Strategy.

This research focuses on the controlling irreversibilities in a radiative, chemically reactive electromagnetohydrodynamics (EMHD) flow of a nanofluid toward a stagnation point. Key considerations include the presence of Ohmic dissipation, linear thermal radiation, second-order chemical reaction with the multiple slips. With these factors, this study aims to provide insights for practical applications where thermal management and energy efficiency are paramount.

Lie group transformation is used to revert the leading partial differential equations into nonlinear ODE form. Hence, the solutions are attained analytically through differential transformation method-Padé and numerically using the Runge–Kutta–Fehlberg method with shooting procedure, to ensure the precise and reliable determination of the solution. This dual approach highlights the robustness and versatility of the methods.

The system’s entropy generation is enhanced by incrementing the magnetic field parameter (M), while the electric field (E) and velocity slip parameters (ξ) control its growth. Mass transportation irreversibility and the Bejan number (Be) are significantly increased by the chemical reaction rate (C_r). In addition, there is a boost in the rate of heat transportation by 3.66% while 0.05⩽ξ⩽0.2; meanwhile for 0.2⩽ξ⩽1.1, the rate of mass transportation gets enhanced by 12.87%.

This paper presents a novel approach to analyzing the entropy optimization in a radiative, chemically reactive EMHD nanofluid flow near a stagnation point. Moreover, this research represents a significant advancement in the application of analytical techniques, complemented by numerical approaches to study boundary layer equations.

This study investigates the influence of capital controls on financial market structure in Sub-Saharan Africa (SSA). This is especially relevant as the former restrictions are relatively common on the sub-continent. At the same time, the sub-region’s financial markets are highly bank-based and focused on the short term, with stock markets being illiquid and stunted.

To achieve its research objectives, the study posits an original model and uses comparative statics to analyze the relation between the aforestated phenomena in a representative SSA economy. Key hypothesized conclusions derived therefrom are tested using panel econometrics.

The comparative static analysis illustrates that capital controls favor banks, making them monopolistic and inefficient. This is confirmed by the empirical investigation, as the said market restriction skews financial market structure towards a bank-dominated system.

The study limits itself to capital controls and their effects on financial market structure. It does not particularly investigate the influence of different types of these restrictions. Specifically, it dichotomizes the influence of the examined controls on bank and stock markets.

The dissimilar influence of capital controls on banks relative to stock markets is critical for decision and policymakers. This paper highlights that capital controls may have unintended adverse effects on domestic financial markets. Also, they may not be the most appropriate policy to deepen markets and enhance domestic resource retention. There is, consequently, a need to determine fitting policies that attract rather than repel financial flows. Furthermore, capital controls may engender rather than address macroeconomic misalignment.

As a social imperative, it is necessary to analyze SSA’s framework of capital restrictions to better understand how they distort market incentives and mechanisms. This would help identify adverse effects that retard social development.

This study extends existing literature by developing a novel analytical framework incorporating key characteristics of SSA economies. This helps to better understand the nature of the capital controls–financial market structure relation in imperfect market conditions.

The paper aims to accurately measure the key motion parameters, such as velocity, azimuth and pitch angle, of the small flying object with a non-uniform curve trajectory. It proposes a measurement method and its calculation model of non-uniform curve trajectory using a photoelectric sensor array.

First, the basic composition of the measurement system and mechanism of photoelectric sensor array are described, respectively. Second, a non-uniform curve mathematical measurement model is constructed differently from the traditional linear trajectory, taking into account the influence of gravity and air resistance. Third, the measurement error of the system is analyzed through numerical simulation. Finally, the accuracy and feasibility of the approach are verified by live-ammunition experiments.

The results show that the systematic error of the hitting point coordinates can be reduced by 9% compared to the traditional linear measurement model. Consequently, this method can meet the higher measurement requirement for the key motion parameters of the small flying object under the non-uniform curve trajectory. Research limitations/implications (if applicable)- although the approach itself is generalizable, the method is unable to detect the motion parameters of multiple small flying objects.

Although the approach itself is generalizable, the method is unable to detect the motion parameters of the multiple small flying objects.

It is evident that the proposed non-uniform curve measurement model is more precise in quantifying the essential characteristics of the small flying object, particularly in consideration of the environmental conditions.

The precise measurement of the key motion parameters of the small flying object can facilitate the enhancement of the protective performance of protective materials.

A novel approach to measurement is proposed, which differs from the conventional uniform trajectory model. To this end, the space construction of the photoelectric sensor array is optimized. The number of the sensors is revised.

In large-scale environments, LIO-SAM (Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping) exhibits poor robustness due to the accumulation of errors caused by factors such as the prevalence of similar surroundings and the lack of features in certain open areas. Therefore, the purpose of this study is to optimize the loop detection module of LIO-SAM to reduce error accumulation and enhance mapping and localization performance.

Based on the LIO-SAM framework, the LinK3D (Linear Keypoints Representation for 3D LiDAR Point Cloud) feature extraction algorithm is integrated in the front end, while the BoW3D (Bag of Words for Real-Time Loop Closing in 3D LiDAR SLAM) loop detection algorithm is integrated in the back end. The features extracted by LinK3D serve as the range factors for the LiDAR, the BoW3D generates loop closure factors and these, along with inertial measurement unit (IMU) preintegration factors and global positioning system (GPS) factors, are added to the factor graph of LIO-SAM. This addition of constraints enhances the mapping and localization effects, optimizing the overall mapping and localization performance.

Based on the electrically controlled car, experiments were conducted in the experimental scenario proposed in this paper. Compared to LIO-SAM, the method presented in this paper significantly reduces cumulative errors. While ensuring real-time performance, it demonstrates superior mapping and localization effects.

This paper proposes and validates a method that integrates LinK3D, BoW3D and LIO-SAM, named LB-LIOSAM, which enhances the accuracy of feature extraction, optimizes the loop detection module of LIO-SAM and improves its mapping and localization performance in specific environmental scenarios.

This study aims to provide a new perspective on the factors determining a country’s tourism performance, understand the interrelationships among these factors and explore their implications for the future of tourism in high-income countries.

The study employs a fuzzy-set qualitative comparative analysis (fsQCA) using five variables from the World Economic Forum’s Travel and Tourism Development Index (TTDI). The focus is on identifying seven configurations of antecedents of Travel and Tourism Industry Gross Domestic Product (T&T Industry GDP).

The study identifies seven configurations of antecedents influencing T&T Industry GDP, revealing how these factors operate in different scenarios, specifically in countries with high and low T&T GDP. These configurations offer insights into potential future pathways for tourism development.

The study implies that tourism is a complex phenomenon influenced by multiple interacting factors. It provides a framework for understanding how different combinations of factors can lead to high or low tourism performance, offering valuable insights for anticipating and shaping the future of tourism.

This study adds value by providing a more nuanced understanding of the tourism industry, challenging the notion of singular effects of variables and highlighting the importance of analyzing multiple, interacting factors in understanding and predicting tourism performance. It contributes to the field of futures studies by offering a tool for anticipating potential future scenarios and their impact on the tourism industry.

It is desired to provide a diversified iterative scheme for solving the constrained solutions of the generalized coupled discrete-time periodic (GCDTP) matrix equations from the perspective of optimization.

The paper considers generalized reflexive solutions of the GCDTP matrix equations by applying the Jacobi gradient-based iterative (JGI) algorithm, which is an extended variant of the gradient-based iterative (GI) algorithm.

Through numerical simulation, it is verified that the efficiency and accuracy of the JGI algorithm are better than some existing algorithms, such as the GI algorithm in Hajarian, the RGI algorithm in Sheng and the AGI algorithm in Xie and Ma.

It is the first instance in which the GCDTP matrix equations are solved applying the JGI algorithm.