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This paper aims to understand the impact of land acquisition and the provision of rehabilitation and remuneration (R & R) transfers included in it, toward the short-run and the long-run growth of an economy as well as on the welfare of farmers and industrialists over time.

The authors develop a two-sector model of growth with agriculture and manufacturing in which land is an essential input to production in both sectors. Industrialists buy land from farmers and deals include R & R payments. Individuals live for one period and at its end, bequeath land and capital assets to their child. There is Hicks-neutral technical progress in each sector.

The R & R policy has no effect on the long-run sectoral growth or land allocation. While such a policy benefits the farmers initially, after a certain period, it reduces their welfare. The R & R scheme makes the industrialist worse-off in all periods. It was found that besides the standard convergence effect, land acquisition by the industrial sector increases the growth rate of capital. This may lead to non-monotonic growth rate of capital.

The two-sector model abstracts from labor and labor markets. Hence, sectoral employment mobility or changes in the skill-wage premium over time are not captured.

First, this paper developed a two-sector growth model with land as a factor of production and an asset. Second, it examined growth and distributive impacts of the R & R package embodied in land transactions.

The paper develops a model for enhancing R&D productivity for Indian public funded laboratories. The paper utilizes the productivity data of five Council of Scientific and Industrial Research (CSIR) laboratories for analysis and to form the constructs of the model.

The weighted average method was employed for analyzing the rankings of survey respondents pertaining to the significant measures enhancing R&D involvement of researchers and significant non-R&D jobs. The authors have proposed a model of productivity. Various individual, organizational and environmental constructs related to the researchers working in the CSIR laboratories have been outlined that can enhance R&D productivity of researchers in Indian R&D laboratories. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to find the predictability of the productivity model.

The organizational factors have a crucial role in enhancing the R&D outputs of CSIR laboratories. The R&D productivity of researchers can be improved through implementing the constructs of the proposed model of productivity.

The R&D productivity model can be adapted by the R&D laboratories to enhance researchers’ R&D involvement, increased R&D outputs and achieving self-sustenance in long run.

The R&D laboratories can initiate exercises to explore the most relevant factors and measures to enhance R&D productivity of their researchers. The constructs of the model can function as a guideline to introduce the most preferable research policies in the laboratory for overall mutual growth of laboratory and the researchers.

Hardly any studies have been found that have focused on finding the measures of enhancing R&D involvement of researchers and the influence of significant time-intensive jobs on researchers’ productivity.

Construction and Demolition (C&D) Waste Management (WM) poses significant challenges in Sri Lanka, contributing to environmental degradation and resource depletion. To address these issues, this study explores the application of Circular Economy (CE) strategies in minimising waste generation and optimising resource utilisation in Sri Lankan construction industry. The research focuses on the construction and building renovation and use and operate stages of the building project life cycle, recognising their significance in waste generation and resource consumption.

The research employed a qualitative approach, utilising the Delphi technique through three rounds of expert interviews. Seventeen experts were involved in the first round, followed by fifteen in the second round, and twelve in the final round. The collected data was analysed using manual content analysis methods.

The research findings revealed fifteen C&D WM issues in the construction and building renovation stage in Sri Lanka, along with suitable strategies to overcome each of them. Similarly, eight C&D WM issues were identified for the use and operate stage of the building, and corresponding strategies were provided to address each issue. By adopting CE strategies such as modular design and material reuse, construction projects can optimise the project's timeline, cost, and quality factors. These strategies enable efficient resource allocation, reduce waste generation, and contribute to the overall sustainability of the project. The impact of CE strategies on mitigating these issues within the project management iron triangle was also discussed.

This paper entails delving into how construction, building renovation, and operation stages of a building's life cycle intersect with CE strategies, which profoundly influence operational efficiency and long-term sustainability. By incorporating principles such as energy efficiency, water conservation, and circular product design, the paper illuminates how these strategies facilitate decreased energy usage, enhanced resource management, and diminished waste production throughout the building's lifespan.

The purpose of this paper is to optimize production of cellulase enzyme from agricultural waste by using Aspergillus fumigatus JCF. The study also aims at the production of bioethanol using cellulase and yeast.

Cellulase production was carried out using modified Mandel’s medium. The optimization of the cellulase production was carried out using Plackett-Burman and Response surface methodology. Bioethanol production was carried out using simultaneous saccharification and fermentation.

Maximum cellulase production at optimized conditions was found to be 2.08 IU/ml. Cellulase was used for the saccharification of three different feed stocks, i.e. sugar cane leaves, corn cob and water hyacinth. Highest amount of reducing sugar was released was 29.1 gm/l from sugarcane leaves. Sugarcane leaves produced maximum bioethanol concentration of 9.43 g/l out of the three substrates studied for bioethanol production.

The present study reveals that by using the agricultural wastes, cellulase production can be economically increased thereby bioethanol production.

This study aims to present a novel system for detection and prevention of black hole and wormhole attacks in wireless sensor network (WSN) based on deep learning model. Here, different phases are included such as assigning the nodes, data collection, detecting black hole and wormhole attacks and preventing black hole and wormhole attacks by optimal path communication. Initially, a set of nodes is assumed for carrying out the communication in WSN. Further, the black hole attacks are detected by the Bait process, and wormhole attacks are detected by the round trip time (RTT) validation process. The data collection procedure is done with the Bait and RTT validation process with attribute information. The gathered data attributes are given for the training in which long short-term memory (LSTM) is used that includes the attack details. This is used for attack detection process. Once they are detected, those attacks are removed from the network using the optimal path selection process. Here, the optimal shortest path is determined by the improvement in the whale optimization algorithm (WOA) that is called as fitness rate-based whale optimization algorithm (FR-WOA). This shortest path communication is carried out based on the multi-objective function using energy, distance, delay and packet delivery ratio as constraints.

This paper implements a detection and prevention of attacks model based on FR-WOA algorithm for the prevention of attacks in the WSNs. With this, this paper aims to accomplish the desired optimization of multi-objective functions.

From the analysis, it is found that the accuracy of the optimized LSTM is better than conventional LSTM. The energy consumption of the proposed FR-WOA with 35 nodes is 7.14% superior to WOA and FireFly, 5.7% superior to grey wolf optimization and 10.3% superior to particle swarm optimization.

This paper develops the FR-WOA with optimized LSTM detecting and preventing black hole and wormhole attacks from WSN. To the best of the authors’ knowledge, this is the first work that uses FR-WOA with optimized LSTM detecting and preventing black hole and wormhole attacks from WSN.

The purpose of this research is to identify the cross-functional factors and their impact after exploratory factor analysis (EFA), especially in B2B context and constructing a model to interpret and quantify the influences (sales performance score) specifically to the IT/ITES companies.

Getting answer for a corporate that where its current stand in the industry is important for the strategy making, especially for the sales team. Few academic researches charted direction toward cross-functional sales factors, but getting answer whether we can quantify that sales performance and identify what is the numeric benchmark value, is difficult. For the companies to understand the need to focus on which cross-functional factors and when, is also difficult.

After 1,079+ literature study, concluded with the 25 antecedents strongly used in previous studies and 8 more on after focused group study, pilot study and discussion with the industry leaders, 35 questions addressing 33 indicators collected in 10 months duration from 310 sales professionals, 90+ IT companies. Three samples were removed as outliers using “Mahalanobis Distance Test” for multivariate analysis, dropped two variables by “Missing value Not at Random” (MNAR). Final 15 determinants of cross-functional sales performance indicators forming four best factors with very high reliability after EFA to form a future formative model and sales performance score.

(1) In this study no moderator and mediator effect are analyzed. (2) This study is the precursor to the final model construction. (3) Business down due to recession, global pandemic, terrorism, earthquake, war etc. are not considered during this analysis and study. Only the cross-functional reasons for natural business down have been considered and analyzed. (4) Exact “Sales Performance Score (SPS)” should be calculated after model forming, adjusting and confirmatory factor analysis.

(1) The major implication of this study would be for IT/ITES companies. It will be very easy for them to quantify the sales performance and measure that scientifically. (2) There will be a way to measure, predict and take measurable actions in case sales performance of the company downfalls. (3) Also the impact will be known to the top management of the company well in advance so that they can make the proper strategy. This will be very useful in current situation when measuring business outcome and make strategy well in advance is of any company's utmost priority.

Focusing on these identified factors companies can improve its sales performance. The authors contribute in creating a statistical model and computing a sales performance score, based on the final factor loading values, would be unique and unprecedented to measure the current industry performance by quantifying its standard or benchmark value for better strategic support toward the achievement of targets.

The purpose of this study is to provide a review of the existing research landscape on work-life balance and women’s career motivation. It examines the relationship between work-life balance and career motivation in the context of Indian women. Specifically, it explores how the work-life balance of women influences the motivational aspects of their careers.

The research uses a systematic literature review to identify and analyze relevant literature on work-life balance and women’s career motivation among Indian women from the Scopus database.

The study uncovers critical insights into the connection between work-life balance and women’s career decisions. It gives insight on how work-life balance significantly impacts women’s career choices. The SLR reveals a notable and consistent upward trend in the domains of work-life balance and career motivation among women.

The findings of this study can inform organizations in tailoring policies that foster women’s career growth while simultaneously supporting a healthy work-life balance. In addition, the research can empower women to make informed decisions about their careers and personal lives. Ultimately, it contributes to creating a more inclusive and gender-equitable work environment, promoting both women’s career aspirations and their overall well-being.

This research stands out in its examination of the relationship between work-life balance and women’s career motivation, particularly in the unique context of Indian women. While previous studies have explored these topics individually, this research bridges the gap by investigating their interplay. Moreover, the application of a systematic literature review approach to these variables in the context of Indian women represents a novel contribution.

The concept of Circular Economy (CE) has gained significant traction in addressing the issue of Construction and Demolition (C&D) waste, which is generated because of global urbanisation and urban renewal. Therefore, this research aims to explore the applicability of CE strategies to minimise the C&D Waste Management (WM) issues in Sri Lanka considering the preconstruction stage of the building project.

The research adopted a qualitative approach, using three expert interview rounds with the Delphi technique. In each round, 17, 15 and 12 experts were involved. A manual content analysis method was used to analyse the collected data.

Findings uncovered effective strategies in CE to address the 14 issues within C&D WM and its effects on the project management iron triangle in Sri Lanka. Integrating CE strategies within the construction sector to tackle C&D WM issues can significantly contribute to establishing a more sustainable, robust and resource-conscious built environment. By adopting CE strategies such as design for adaptability of existing buildings and design for disassembly, construction projects can optimise the project's timeline, cost and quality factors.

This will help to minimise the demand for virgin materials and reduce the volume of waste generated. Using recycled materials also helps close the loop of the materials cycle, thereby contributing to the CE. Also, this research contributes uniquely by offering practical, context-driven solutions that align with Sri Lanka’s construction sector.

This study aims to provide insight into the operational factors of big data. The operational indicators/factors are categorized into three functional parts, namely synthesis, speed and significance. Based on these factors, the organization enhances its big data analytics (BDA) performance followed by the selection of data quality dimensions to any organization's success.

A fuzzy analytic hierarchy process (AHP) based research methodology has been proposed and utilized to assign the criterion weights and to prioritize the identified speed, synthesis and significance (3S) indicators. Further, the PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluations) technique has been used to measure the data quality dimensions considering 3S as criteria.

The effective indicators are identified from the past literature and the model confirmed with industry experts to measure these indicators. The results of this fuzzy AHP model show that the synthesis is recognized as the top positioned and most significant indicator followed by speed and significance are developed as the next level. These operational indicators contribute toward BDA and explore with their sub-categories' priority.

The outcomes of this study will facilitate the businesses that are contemplating this technology as a breakthrough, but it is both a challenge and opportunity for developers and experts. Big data has many risks and challenges related to economic, social, operational and political performance. The understanding of data quality dimensions provides insightful guidance to forecast accurate demand, solve a complex problem and make collaboration in supply chain management performance.

Big data is one of the most popular technology concepts in the market today. People live in a world where every facet of life increasingly depends on big data and data science. This study creates awareness about the role of 3S encountered during big data quality by prioritizing using fuzzy AHP and PROMETHEE.

Strengthening ESG strategies in Malaysian banks is necessary as they continue to face difficulties integrating ESG into their strategies and disclosure despite existing government frameworks. This study aims to use stakeholder-resource-based view (RBV) concept to explore how board characteristics and ownership concentration influence ESG disclosure practices in Malaysian banks.

The study analysed annual, environmental, social and governance (ESG) and integrated reports of Malaysian banks from 2010 to 2022 to examine the effects of board characteristics on ESG disclosures. Using content analysis and 481 balanced data sets, ordinary least squares (OLS) and robust regressions were applied, with interaction terms testing the moderating effects of ownership concentration.

Board independence negatively impacts ESG disclosure in Malaysian banks, suggesting that independent directors may not prioritise sustainability. Board size, diversity and sustainability committees positively influence ESG practices. Ownership concentration interactions reinforce these findings, but board independence remains negatively significant.

Future research should expand the sample to other emerging markets, explore a wider range of bank board attributes and use advanced econometric methods to increase the generalisability of the results.

The study impacts theory, financial institutions and policy, redefining ESG practices in Malaysian banking. It highlights the role of board characteristics and the importance of ownership concentration. Several practical recommendations are provided.

The study impacts theory, financial institutions and policy by redefining ESG practices within Malaysian banking. It highlights the significance of board characteristics and ownership concentration, offering several practical recommendations.

The study fills gaps in the literature by examining the impact of board characteristics on ESG disclosures through content and statistical analyses. It integrates stakeholder theory with RBV to provide novel insights into ESG reporting in Malaysian banks, highlighting the role of high ownership concentration in emerging markets.