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The purpose of this paper is to apply an efficient hybrid computational numerical technique, namely, q-homotopy analysis Sumudu transform method (q-HASTM) and residual power series method (RPSM) for finding the analytical solution of the non-linear time-fractional Hirota–Satsuma coupled KdV (HS-cKdV) equations.

The proposed technique q-HASTM is the graceful amalgamations of q-homotopy analysis method with Sumudu transform via Caputo fractional derivative, whereas RPSM depend on generalized formula of Taylors series along with residual error function.

To illustrate and validate the efficiency of the proposed technique, the authors analyzed the projected non-linear coupled equations in terms of fractional order. Moreover, the physical behavior of the attained solution has been captured in terms of plots and by examining the L₂ and L_∞ error norm for diverse value of fractional order.

The authors implemented two technique, q-HASTM and RPSM to obtain the solution of non-linear time-fractional HS-cKdV equations. The obtained results and comparison between q-HASTM and RPSM, shows that the proposed methods provide the solution of non-linear models in form of a convergent series, without using any restrictive assumption. Also, the proposed algorithm is easy to implement and highly efficient to analyze the behavior of non-linear coupled fractional differential equation arisen in various area of science and engineering.

The Indian power sector is dominated by coal. Environmental awareness and advances in techno-economic front have led to a slow but steady shift towards greener alternatives. The distributions of both fossil fuel resources and renewable energy potential are not uniform across the states. Paper attempts to answer how the states are performing in the sector and how the renewable energy and conventional resources are affecting the dynamics.

The authors employ a two-stage data envelopment analysis (DEA) to rank the performance of Indian states in the power sector. Multi-stage analysis opens up the DEA black-box through disaggregating power sector in two logical sub-sectors. The performance is evaluated from the point-of-view of policy formulating and implementing agencies. Further, an econometric analysis using seemingly unrelated regression equations (SURE) is conducted to estimate the determinants of total and industrial per-capita electricity consumption.

Efficiency scores obtained from the first phase of analysis happens to be a significant explanatory variable for power consumption. The growth in electricity consumption, which is necessary for economic wellbeing, is positively affected by both renewable and non-renewable sources; but conventional sources have a larger impact on per-capita consumption. Yet, the share of renewables in the energy mix has positive elasticity. Hence, the findings are encouraging, because development in storage technologies, falling costs and policy interventions are poised to give further impetus to renewable sources.

The study is one of the very few where entire spectrum of the Indian power sector is evaluated from efficiency perspective. Further, the second phase analysis gives additional relevant insights on the sector.

While the potential of information and communication technology (ICT) for poverty reduction is widely recognised, limited knowledge exists on its use in the social protection schemes devised for the world’s poor. Drawing on the institutionalist vision of IS development and organisational change put forward by Avgerou (2000), the authors propose that computerisation of these schemes entails two processes, namely, the progressive affirmation of ICT innovation and a shift in the programmes' organisational structure, which moves from a subsidy-based model to one grounded on direct cash transfers. The purpose of this paper is to illustrate how the role of ICT in anti-poverty schemes results from concomitance of such processes.

The paper draws on a study of the public distribution system (PDS), the main food security scheme in India, as it is being computerised in the state of Karnataka. Following an interpretive case study methodology, it investigates the ongoing computerisation of the Karnataka PDS through a combination of back-end and front-end technologies, based on biometric recognition of the programme’s users.

The data reveal that transformation of the PDS results from the simultaneous processes of institutionalisation of ICT innovation and deinstitutionalisation of the extant state-led subsidy scheme, in favour of a leaner social protection system centred on cash transfers to beneficiaries. This illustrates the point that ICT innovation is intertwined with the decline of an extant social welfare structure and the rise of a new one, based on the direct transfer of benefits.

The paper offers a new theoretical perspective to illuminate the computerisation of anti-poverty programmes, a phenomenon that affects the entitlements of millions of poor people on a global scale. In parallel, it draws practical implications for countries embarking on the digitalisation of their social protection schemes.

This paper aims to show that the meaning of development influencing the design of ICT for development (ICT4D) projects is important in deciding what purpose they will eventually serve.

Through a review of the literature on development and technology studies, the paper shows how different meanings of development guide technology usage and policy choice for land reforms. A case study of a land records computerization project in India is used to reinforce this claim.

By explaining alternative manifestations of interlinkages between development and technology, the paper demonstrates that the design choice, especially the content and service delivery model, for an ICT4D project gets influenced by the development context within which it is set.

The focus of the paper has been restricted to a limited context of information and communication technology usage – to land reforms as a development objective, in a relatively better‐off province of India. Future research will include ICT4D projects in other domains and in different socio‐economic settings.

The findings will encourage ICT4D policy makers and project designers to broaden their perspectives of what constitutes development and explicitly acknowledge the importance of development contexts in influencing the outcomes of ICT4D projects.

Prior research in ICT4D has not looked explicitly at the influence of development contexts in informing technology design. The paper attempts to fill this gap by tracing design choices to the contexts of technology use created through alternative understanding of the objectives of development. This can be of help to researchers looking at issues of technology use for societal development and for policy makers and project designers entrusted with the choice of technology.

E-commerce.

The case study is specific to the marketing demographics of online Indian shoppers and therefore, the inter-relationship between certain customer requirements and design elements and the relative importance of items in the latter may not follow the same pattern elsewhere.

At a time when e-commerce is booming in India and when online retailers are posting multifold year-on-year growth, it becomes increasingly important to identify the factors pertaining to online stores which can influence the buying behavior of consumers. This case aims to explore such factors relevant to businesses as well as consumers so as to enable the next generation of leaders in online retail business to gain maximally. It deals with critical design characteristics of online retail stores in India which can prove crucial to their success. These characteristics are manifestations of various customer requirements. Two surveys are conducted to establish a hierarchy of design elements and quantify the inter-relationships between customer requirements and design characteristics. This is followed by leads as to which factors may or may not have contributed toward the declining sales volume of an e-commerce start-up, namely, E-Bazaar.

The learning objectives of the case include: the study of design characteristics with respect to their relative importance; the analysis of the degree of relationships between the design characteristics and customer requirements; and the interpretation of real-life signs in taking strategic business decisions in the field of e-commerce. The case aims to prepare a new breed of leaders in the e-commerce sector with a good level of relevant business acumen to help them make informed strategic choices.

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Considering the swift adoption of innovative sustainability practices in businesses to accomplish sustainable development goals (SDGs), research on corporate sustainability has increased significantly over the years. This research intends to analyze the published literature, emphasizing the existing, emerging and future research directions on achieving the SDGs through corporate sustainability.

This research analyzed the growing trends in corporate sustainability by incorporating 2,038 Scopus articles published between 1999 and 2022 using latent Dirichlet allocation (LDA) topic modeling, bibliometrics and qualitative content analysis techniques. The bibliometric data were analyzed using performance and science mapping. Thereafter, topic modeling and content analysis uncovered the topics included under the corporate sustainability umbrella.

The findings indicate that investigation into corporate sustainability has considerably increased from 2015 to date. Additionally, the majority of studies on corporate sustainability are from the United States of America, the United Kingdom and Germany. Besides, the USA has the most collaboration in terms of co-authorship. S. Schaltegger was considered the most productive author. However, P. Bansal was ranked as the top author based on a co-citation analysis of authors. Further, bibliometric data were evaluated to analyze leading publications, journals and institutions. Besides, keyword co-occurrence analysis, topic modeling and content analysis highlighted the theoretical underpinnings and new patterns and provided directions for further research.

This study demonstrates various existing and emerging themes in corporate sustainability, which have various repercussions for academicians and organizations. This research also examines the lagging themes in the current domain.

Despite the extensive benefits of human resource (HR) analytics, the intention to adopt such technology is still a matter of concern in the engineering and construction sectors. This study aims to examine the slow adoption of HR analytics among HR professionals in the engineering and construction sector.

A cross-sectional online survey including 376 HR executives working in Indian-based engineering and construction firms was conducted. Hierarchal regression, structural equation modeling and artificial neural networks (ANN) were applied to evaluate the relative importance of HR analytics predictors.

The results reveal that hedonic motivation (HM), data availability (DA) and performance expectancy (PE) influence the behavioral intention (BI) to use HR analytics, whereas effort expectancy (EE), quantitative self-efficacy (QSE), habit (HA) and social influence (SI) act as barriers to its adoption. Moreover, PE was the most influential predictor of BI.

Based on the findings of this study, engineering and construction industry managers can formulate strategies for the implementation and promotion of HR analytics to enhance organizational performance.

This study draws attention to evidence-based decision-making, emphasizing barriers to the adoption of HR analytics. This study also emphasizes the concept of DA and QSE to enhance adoption among HR professionals, specifically in the engineering and construction industry.

HR analytics is a process for systematic computational analysis of data or statistics. It discovers, interprets and communicates significant patterns in data to enable evidence-based HR research and uses analytical insights to help organizations achieve their strategic objectives. However, its adoption and utilization among HR professionals remain a subject of concern. This study aims to determine the reasons that facilitate or inhibit the acceptance of HR analytics among HR professionals in the banking, financial services and insurance (BFSI) sector.

A sample of 387 HR professionals in BFSI firms across India was collected through non-probabilistic purposive sampling. Structural equation modeling was applied to analyze the association between predetermined variables. In addition, the predictive relevance of “Data Availability” was analyzed using hierarchical regression.

The results revealed that data availability, hedonic motivation and performance expectancy positively influenced behavioral intention (BI). In contrast, effort expectancy, social influence and habit had an insignificant effect on BI. Also, facilitating conditions (FCs), habit, BI achieved a variance of 60% in HR analytics use. The use behavior of HR analytics was significantly influenced by FCs and BIs.

This study focuses on insights into the elements that influence HR analytics adoption, revealing additional light on success drivers and grey areas for failed adoption.

This research adds to the body of knowledge by identifying factors that hinder the adoption of HR analytics in Indian organizations and signifies the relevance of easy accessibility and availability of data for technology adoption.

This study aimed to evaluate the factors that determine an individual's decision to adopt human resources (HR) analytics. This study attempts to extend Unified Theory of Acceptance and Use of Technology - 2 (UTAUT2) to identify the lag rate in adoption.

Responses were obtained from 387 HR employees of the Banking Financial Services and Insurance (BFSI) sector in metropolitan cities of India through nonprobabilistic purposive sampling. The analysis was performed through hierarchical regression, structural equation modeling and moderation of resistance to change.

The results suggest that performance expectancy, hedonic motivation and data availability are endorsed by proponents of the intention to adopt HR analytics. In contrast, effort expectancy, social influence, quantitative self-efficacy and habits did not influence behavioral intention (BI). Additionally, the actual use behavior (UB) of HR analytics was determined by BI and facilitating conditions. Furthermore, the moderating effect of resistance to change is explored.

This study makes a significant contribution to the literature on the adoption of HR analytics. By appropriately concentrating on the adoption intention of HR analytics, organizations can intensify healthy employee relationships, thus encouraging the actual usage of HR analytics.

This study formulates a conceptual framework for the adoption of HR analytics that can be used by top management to formulate strategies for the implementation of HR analytics. Moreover, this study aimed to expand UTAUT2, emphasizing the concept of data availability and quantitative self-efficacy and examining the moderating role of resistance to change in the relationship between BI and UB.

This study aims to analyze the existing literature in human resource analytics and highlights the future research agenda and trends in the same context. It deals with evaluating regional distribution, identifying key authors, publications, journals and keyword occurrences while examining current literature.

A total of 127 articles exported from the Scopus database were systematically analyzed using bibliometric analysis through VOSviewer, including performance analysis and science mapping of the literature studied.

This research postulates the inconsistency between the number of publications and citations received by an author. There was an increase in collaborative research over the years. Human Resource Management Review was regarded as the most influential journal with maximum citation. Maximum publications came from Asian countries. The study revealed that the author with maximum citation were mostly the first authors of the most cited documents.

This research may be beneficial for both researchers and human resource (HR) practitioners because it identifies the research gaps and research needs in the HR analytics domain. Besides, this study recognizes the patterns in HR analytics literature that helps researchers better understand the subject area.

This research incorporates bibliometric analysis for analyzing HR analytics literature to establish a more exhaustive and systematic understanding of the research area. This research contributes to the existing body of literature and assists fellow researchers in future studies.