This book compiles current research relating to business ethics within developing markets around the world, featuring research on topics essential to remaining competitive in the modern global marketplace, such as corporate social responsibility, corporate governance, consumer behavior understanding, and ethical leadership.

Inconsistent corporate social responsibility (CSR) practices across stakeholder groups may induce undesired consequences for the firm. This study investigates the longitudinal and differential effect of chief executive officer (CEO) tenure on external and internal CSR and the moderating effects of two important contingencies relevant to the firm's social investments: firm visibility and slack availability. It presents CEO tenure as an important upper echelon factor that may induce differential preferences toward external and internal CSR and, therefore, CSR inconsistencies. Accordingly, it proposes (...) two important and relevant contingencies and provides additional evidence on how a firm's visibility and slack availability could affect CEO tenure-related differential behaviors. The findings contribute to studies on the temporal orientations of CEOs and how they impact firm strategic behavior. They also contribute to the literature on firm visibility and slack and how they may interact with certain upper echelon characteristics and affect firm behaviors. The analysis cautions against the perceptions of the relationships between firm- and CEO-level variables and a firm's aggregate CSR. (shrink)

The two-wheeled self-balancing robot is based on the axletree and inverted pendulum. Its balancing problem requires a control action. To speed up the response of the robot and minimize the steady state error, in this article, a grey wolf optimizer method is proposed for TWSBR control based on state space feedback control technique. The controller stabilizes the balancing robot and minimizes the overshoot value of the system. The dynamic model of the system is derived based on Euler formula and linearized (...) to state space representation to enhance the control technique. Then, the GWO optimizes the state feedback controller parameters. Simulation results show that the system reaches the zero steady-state error with less than 2 ms, which proves the effectiveness of the proposed controller over the classical state feedback controller in terms of fast response, very small overall error, and minimum overshoot. (shrink)

The Sustainable Development Goal of the United Nations related to reduced inequalities calls for greater economic inclusion of the poor. Yet, how business leaders grant economic opportunities and development to the poor is significantly under-researched. Extending burgeoning responsible leadership theory that promotes paradox-savvy leadership for building inclusive ventures through various actors, this study introduces new concepts of inclusive leadership that foster the economic inclusion of the poor from Amartya Sen’s capability approach perspective. By studying how leaders include the poor in (...) social businesses, we provide a fresh perspective of inclusive leadership as a personalized empowering cycle of economic–social–economic inclusion to close the gaps between the rich and poor in business and society. This perspective provides new territories of diversity and inclusion research for reduced inequality. (shrink)

Modern optimisation is increasingly relying on meta-heuristic methods. This study presents a new meta-heuristic optimisation algorithm called Eurasian oystercatcher optimiser (EOO). The EOO algorithm mimics food behaviour of Eurasian oystercatcher (EO) in searching for mussels. In EOO, each bird (solution) in the population acts as a search agent. The EO changes the candidate mussel according to the best solutions to finally eat the best mussel (optimal result). A balance must be achieved among the size, calories, and energy of mussels. The (...) proposed algorithm is benchmarked on 58 test functions of three phases (unimodal, multimodal, and fixed-diminution multimodal) and compared with several important algorithms as follows: particle swarm optimiser, grey wolf optimiser, biogeography based optimisation, gravitational search algorithm, and artificial bee colony. Finally, the results of the test functions prove that the proposed algorithm is able to provide very competitive results in terms of improved exploration and exploitation balances and local optima avoidance. (shrink)

As a futuristic emblem, smart cities represent a goal to provide all of the services required for a high-quality existence while conserving natural resources to the maximum extent possible. It turns out that the "Line City in Saudi Arabia" is the most famous and modern of these smart cities in terms of preserving 100 percent natural life, owing to the fact that they rely totally on natural energy and do not use any automobiles. The issues and challenges that have been (...) highlighted will assist in the improvement of municipal management. One of the most generally implemented projects in the field of smart cities is the technological and integrative developments of the use of sensors and data collecting in conjunction with rising difficulties aimed at enhancing human well-being and improving human livelihood. This is especially true in Saudi Arabia, where visitors can arrive quickly by just walking through the checkpoints, resulting in a journey of little more than a few minutes to reach any regular destination. It also splits the city into many different levels of the ground, enabling for the conservation of natural excess energy. (shrink)

Sudies on Buddhist philosophy and Vedanta philosophy of Śaṅkarācārya.

The potential of the soil to hold plant nutrients is governed by the cation-exchange capacity of any soil. Estimating soil CEC aids in conventional soil management practices to replenish the soil solution that supports plant growth. In this study, a multiple model integration scheme supervised with a hybrid genetic algorithm-neural network was developed and employed to predict the accuracy of soil CEC in Tabriz plain, an arid region of Iran. The standalone models and extreme learning machine ) were implemented for (...) incorporation into the MM-GANN. In addition, it was tested to enhance the prediction accuracy of the standalone models. The soil parameters such as clay, silt, pH, carbonate calcium equivalent, and soil organic matter were used as model inputs to predict soil CEC. With the use of several evaluation criteria, the results showed that the MM-GANN model involving the predictions of ELM and ANN models calibrated by considering all the soil parameters as inputs provided superior soil CEC estimates with a Nash Sutcliffe Efficiency = 0.87, Root Mean Square Error = 2.885, Mean Absolute Error = 2.249, Mean Absolute Percentage Error = 12.072, and coefficient of determination = 0.884. The proposed MM-GANN model is a reliable intelligence-based approach for the assessment of soil quality parameters intended for sustainability and management prospects. (shrink)