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The purpose of this paper is to share the perspective of CEO and Vice Chairman of Hexaware Technologies, P.R. Chandrasekar, while exploring the question, “Does South Asia matter?”

The paper followed an interview format and utilized P.R. Chandrasekar's responses to guide and inform the discussion on South Asia.

This paper found that South Asia does matter, and always has.

This paper offers the perspective of a CEO of a multinational corporation with global experience and vast knowledge of the South Asian region. His first‐hand experiences add much value to the discussion on South Asia.

This paper aims to investigate the feasibility of developing an eco-friendly dyeing process for a regenerated polyester fiber (polytrimethylene terephthalate) using a natural dye (Lac) and bio-mordant.

The effects of temperature, time, initial pH of dye bath, material to liquor ratio and mordant concentration on color strength of polytrimethylene terephthalate fiber dyed with Lac were examined. The results were compared using three bio-mordant (catechu, myrobalan and pomegranate) and three inorganic mordant (alum, ferrous sulfate and stannous chloride). Single replicate of 25-design methodology was used to identify three significant factors affecting color strength, and optimization was done using response surface methodology based on 2³-central composite rotatable design.

Color strength achieved using catechu as a bio-mordant was close to that with ferrous sulfate and higher than with stannous chloride. Temperature, initial pH and mordant concentration were identified as significant factors affecting color strength of dyed fiber with catechu. Optimization revealed temperature of 133OC, initial pH of 6 and bio-mordant (Catechu) concentration of 10 per cent to be the optimal conditions for dyeing, with K/S value of 4.55.

The study revealed the possibility of satisfactory dyeing of regenerated polyester fibers with natural dyes, replacing disperse dyes. The comparison of color strength achieved indicated the possibility of replacing inorganic mordant with bio-mordant in such dyeing process. The dyeing process could thus be made more eco-friendly by removal of toxic chemicals from effluents.

The purpose of this paper is to investigate the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.

The differential inequality theory and some novel mathematical analysis techniques are applied.

A set of sufficient conditions which guarantee the existence and global exponential stability of periodic solution of involved model is derived.

It plays an important role in designing the neural networks.

The obtained results of this paper are new and complement some previous studies. The innovation of this paper concludes two aspects: the analysis on the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays is first proposed; and it is first time to establish the sufficient criterion which ensures the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.

History has taught us that every aspect of the world around us is changing. Right from its formation, the earth has been evolving climatically, edaphically, and biotically to its present state. The forcing for all these changes in the past was natural, and human activities had least influence till the industrial revolution. Since the beginning of the 18th century, human activities associated with the industrial revolution have changed the composition of the atmosphere and thereby having a greater influence on the earth's climate. The use of fossil fuels like coal and oil coupled with deforestation has increased the concentration of heat-trapping “greenhouse gases,” which prevent the heat from the earth escaping to space. Because of this, the very greenhouse gases, which helped sustain life on the earth under normal circumstances, have become detrimental due to its higher concentration. Several models have predicted that the rising concentrations of greenhouse gases produce an increase in the average surface temperature of the earth over time. Rising temperatures may, in turn, produce changes in precipitation patterns, storm severity, and sea level, commonly referred to as “climate change.” The Intergovernmental Panel on Climate Change (IPCC) defines climate change broadly as “any change in climate over time whether due to natural variability or as a result of human activity.” The United Nations Framework Convention on Climate Change (UNFCCC) defines climate change as “a change of climate that is attributed directly or indirectly to human activity, that alters the composition of the global atmosphere, and that is in addition to natural climate variability over comparable time periods.”

Electronic devices aid communication during new communication phases and the scope of cognitive radio networks has changed communication paradigms through efficient use of spectrums. The communication prototype of cognitive radio networks defines user roles as primary user and secondary user in the context of the spectrum allocation and use. The users who have licensed authority of the spectrum are denoted as primary users, while other eligible users who access the corresponding spectrum are secondary users.

The multiple factors of transmission service quality can have a negative influence due to improper scheduling of spectrum bands between primary users and secondary users. There are considerable contributions in contemporary literature concerning spectrum band scheduling under spectrum sensing. However, the majority of the scheduling models are intended to manage a limited number of transmission service quality factors. Moreover, these service quality factors are functional and derived algorithmically from the current corresponding spectrum. However, there is evidence of credible performance deficiency regarding contemporary spectrum sensing methods

This article intends to portray a fuzzy guided integrated factors-based spectrum band sharing within the spectrum used by secondary users. This study attempts to explain the significance of this proposal compared to other contemporary models.

This article intends to portray a fuzzy guided integrated factors-based spectrum band sharing within the spectrum used by secondary users. This study attempts to explain the significance of this proposal compared to other contemporary models.

The purpose of this paper is to develop an algorithm, using PCA‐based neural network, to retrieve the vertical rainfall structure in a precipitating atmosphere. The algorithm is powered by a rigorous solution to the plane parallel radiative transfer equation for the atmosphere with thermodynamically consistent vertical profiles of humidity, temperature and cloud structures, together with “measured” vertical profiles of the rain structure derived from a radar.

The raining atmosphere is considered to be a plane parallel, radiatively participating medium. The atmospheric thermodynamic profiles such as pressure, temperature and relative humidity along with wind speed at sea surface and cloud parameters corresponding to Nargis, a category 4 tropical cyclone that made its landfall on May 2, 2008 at the Republic of Myanmar, are obtained by solving the flux form of Euler's equations in three‐dimensional form. The state‐of‐the‐art community software Weather Research and Forecasting has been used for solving the set of equations. The three‐dimensional rain profiles for the same cyclone at the same instant of time are obtained from National Aeronautics and Space Administration's space borne Tropical Rainfall Measuring Mission's precipitation radar over collocated pixels. An in‐house Micro‐Tropiques code is used to perform radiative transfer simulations for frequencies corresponding to a typical space borne radiometer, and hence to generate the database which is later used for training the neural network. The back propagation‐based neural network is optimized with reduced number of parameters using principal component analysis (PCA).

The results show that neural network is capable of retrieving the vertical rainfall structure with a correlation coefficient of over 0.99. Further, reducing the ill‐posedness in retrieving 56 parameters from just nine measurements using PCA has improved the root mean square error in the retrievals at reduced computational time.

The paper shows that combining numerically generated atmospheric profiles together with radar measurements to serve as input to a radiative transfer model brings in the much‐required synergy between numerical weather prediction, radar measurements and radiative transfer. This strategy can be gainfully used in satellite meteorology. Using principal components to reduce the ill‐posedness, thereby increasing the robustness in retrieving vertical rain structure, has been attempted for the first time. A well‐trained network can be used as one possible option for an operational algorithm for the proposed Indian climate research satellite Megha‐Tropiques, due to be launched in early 2011.

Artificial Intelligence (AI) is one of the newest technology that is quickly advancing and can be utilised to improve human resource competence in the age of rapid digital transformation. The present competitive scenario demands accurate data that need to be collected and analysed for organisational growth.

Purpose: The research examines the applications and usage of AI in performance management and further analyses the future of PM from the perspectives of AI.

Methodology: The study is conceptual and relies on secondary data from research papers, publications, HR blogs, survey reports and other sources. Employee performance and attitudes were monitored using digital technologies, big data analytics and AI. The quality of employee performance continues to increase with the integration of AI, enabling predictive analytics to increase employee performance.

Research Implication: In employee performance appraisal, a digital performance management system leads to openness and honesty with time, effort and sincerity. It is based on the performance management system’s practical usefulness.

Theoretical Implication: The study’s findings provide HR managers, academics, IT professionals and practitioners with an understanding of how AI may be used for performance management and its consequences on their operations. In addition, the connection between the HR devolution theory on performance management and AI is discussed.

The main purpose of this study is to examine the synergistic impact of marketing orientation (MO) and strategic orientation (SO) on business performance (BP) and to explore role of entrepreneurial qualification (moderating) and SO (mediating) in MO and BP relationship.

Nine hundred small and medium-sized enterprises (SMEs) owners/managers operating in Jammu District, North India, are contacted during October 2013 to February 2014.

The study identifies and confirms MO (marketing strategy, customer philosophy, operational efficiency and integrated marketing) and SO (defensive, proactive, analytical and risk-averse) as multi-dimensional constructs. Although both orientations have positive impact on SMEs performance, however, their synergistic impact is weak. In addition, the study also reveals that MO has direct and indirect impact (through SO) on BP. Lastly, there exists moderating role of entrepreneurial qualification between MO and SO.

The major limitation of the study is the focus on SMEs. Based on the strength of the relationships among the dimensions and sub-dimensions of the MO, SO and BP, replication and validation of research in service sector across the country and globe is required to generalise the results and to develop stronger theory.

This is the first empirical study to investigate the synergistic impact of two well-established notions – MO and SO. It provides empirical evidence for the claim that synergistic impact of marketing and SO on BP is weak, unlike their respective strong impact on BP. This study also clarifies roles of entrepreneurial qualification and SO in MO and BP relationship.

The purpose of this paper (editorial) is to provide a balanced contextual overview of several South Asian countries, in order to present their relevance in international business research.

The author argues that South Asia offers a rich context for studying and advancing international business theory and practice.

South Asia presents an interesting paradox; where dynamism and growing challenges (of poverty, corruption, inadequate governance and extremism) exist side by side. The author also discusses that using South Asia as a context of the study is likely to add relevance and rigor to international business theory, therefore addressing the recent calls by many scholars.

Countries in South Asia are under‐researched by many accounts. Hence an exploration of business and management issues is likely to expose phenomena that have the potential to advance international business theory and practice.

This editorial highlights the regional importance of South Asia in international business research. It places South Asian Journal of Global Business Research, with its emphasis on South Asian economies, organizations, diaspora and people, as an important journal for developing a body of knowledge relating to South Asian business practices, deepening our understanding of South Asia, broadening our view of international business theory and research, identifying new phenomena, exploring indigenous methodological tools and increasing the output of research focused on the region that appears in and also has an impact on global research.