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Land value in urban areas in India is influenced by regulations, bylaws and the amenities associated with them. Planning interventions play a significant role in enhancing the quality of the neighbourhood, thereby resulting in a change in its value. Land is a distinct commodity due to its fixed location, and planning interventions are also specific to certain locations. Consequently, the factors influencing land value will vary across different areas. While recent literature has explored some determinants of land value individually, conducting a comprehensive study specific to each location would be more beneficial for making informed policy decisions. Therefore, this article aims to examine and identify the critical factors that impact the value of residential land in the National Capital Territory of Delhi, India.

The study employed a combination of semi-structured and structured interview methods to construct a Relative Importance Index (RII) and ascertain the critical determinants affecting residential land value. A sample of 36 experts, comprising property valuers, urban planners and real estate professionals operating within the National Capital Territory of Delhi, India, were selected using snowball sampling techniques. Subsequently, rank correlation and ANOVA methods were employed to evaluate the obtained results.

Location and stage of urban development are the most critical determinants in determining residential land values in the National Capital Territory of Delhi, India. The study identifies a total of 13 critical determinants.

A scenario planning approach can be developed to achieve an equitable distribution of values and land use entropy. A land value assessment model can also be developed to assist professional valuers.

There has been a lack of emphasis on assessing the impact of planning interventions and territorial regulation on land values in the context of Delhi. This study will contribute to policy decision-making by developing a rank list of planning-based determinants of land value.

The present study investigates the impact of digital entrepreneurial education and training and its impact on the digital entrepreneurial intention (EI) through the mediating character of entrepreneurial competence.

A total of 391 survey responses were collected from employees using convenient and snowball sampling methods.

Digital entrepreneurial education and training showed a positive influence on entrepreneurial competence and EI, with entrepreneurial competence mediating the relationship between digital entrepreneurial education and training practices and EI.

This study is intended to assist the development of digital entrepreneurs. The implications of this study are also useful for governments, entrepreneurs, venture capitalists, angel investors and various international development institutions.

The novelty of this study relates to exploring the relationship between digital entrepreneurial education and training, entrepreneurial competence and digital EI.

The accelerating business transformation through Industry 4.0 (I4.0) is expected to create significant value in the manufacturing industry by delivering considerably high productivity, superior quality, better efficiency and effectiveness. However, its evolutionary processes have far-reaching challenging for humanity. This has triggered a need to analyze the impact of I4.0 on various people-centric variables (PCVs).

This paper attempts to analyze the interrelationship dynamics between the PCVs in the current digital-industry ecosystem using a focus-group approach and causal loop diagrams. Application of the SWARA (stepwise weight assessment ratio analysis) methodology has provided its prioritized ranking in terms of importance.

The study has highlighted that I4.0 has a significant influence on five of the 13 PCVs – human quality of life, digital dexterity, high-skilled talent, low-skilled employment and creativity which contribute to 80% of the total impact.

The prioritized weights of the human factors from the SWARA approach have facilitated the assessment of the Human Resource Development Index (HRDI). The study is also contributing in enriching the literature on the human impact of the growing I4.0 and triggered the researchers to study further its adverse impact on critical human factors.

1. The paper pertains to debates on a very critical issue of impact of integration of the current intelligent digital technologies in manufacturing and services to transform businesses to be more flexible and agile.

2. This paper features I4.0 as a technology that allows integration of new products in the existing production lines, one-off manufacturing runs and high mix manufacturing.

3. The paper also highlights major adjustments in operational activities, processes, supply chain, and organizational redesign due to I4.0 adoption.

4. The current research study has significantly enriched the literature on the I4.0 impact on people-centric variables (PCVs) using the SWARA method. The use of the Causal Loop Diagram has very aptly brought out the type of causality (polarity) between the different PCVs in the growth of I4.0.

The paper pertains to debates on a very critical issue of impact of integration of the current intelligent digital technologies in manufacturing and services to transform businesses to be more flexible and agile.

This paper features I4.0 as a technology that allows integration of new products in the existing production lines, one-off manufacturing runs and high mix manufacturing.

The paper also highlights major adjustments in operational activities, processes, supply chain, and organizational redesign due to I4.0 adoption.

The current research study has significantly enriched the literature on the I4.0 impact on people-centric variables (PCVs) using the SWARA method. The use of the Causal Loop Diagram has very aptly brought out the type of causality (polarity) between the different PCVs in the growth of I4.0.

Blockchain technology (BCT) has emerged as a powerful tool for enhancing transparency and trust. However, the relationship between the benefits of BCT and agri-food supply chain performance (AFSCperf) remains underexplored. Therefore, the current study investigates the influence of BCT on AFSCperf and sustainability issues.

Through a comprehensive literature review, various benefits of BCT are identified. Subsequently, a research framework is proposed based on data collected from questionnaire surveys and personal visits to professionals in the agri-food industry. The proposed framework is validated using partial least square structural equation modelling (PLS-SEM).

The findings reveal that BCT positively impacts AFSCperf by improving traceability, transparency, food safety and quality, immutability and trust. Additionally, BCT adoption enhances stakeholder collaboration, provides a decentralised network, improves data accessibility and yields a better return on investment, resulting in the overall improvement in AFSCperf and socio-economic sustainability.

This study offers valuable practical insights for practitioners and academicians, establishing empirical links between the benefits of BCT and AFSCperf and providing a deeper understanding of BCT adoption.

Stakeholders, managers, policymakers and technology providers can leverage these findings to optimise the benefits of BCT in enhancing AFSCperf. Moreover, it utilises rigorous theoretical and empirical approaches, drawing on a multidisciplinary perspective encompassing food operations and supply chain literature, public policy, information technology, strategy, organisational theory and sustainability.

This study aims to examine the relationship between tool adoption and information literacy within smallholder farmers (SHFs).

A structured questionnaire was used to gather data for this quantitative study from 225 SHFs. Structural equation modelling was done to test the hypotheses.

The findings established that tool adoption dimensions (Information and communication technologies (ICT) acceptance, language use and information culture) positively and significantly influenced information literacy. Information culture had the strongest impact.

The study enriches the situated learning theory (SLT) literature by introducing tool adoption as a predictor of information literacy in a new context of SHFs. Use of tools as independent variables is a positive deviation from previous studies that have used them as mediating variables. Despite the contributions, the cross-sectional design study undermines the ability to solicit more detailed perspectives from the lived in experience of the respondents.

Managers should promote usage of context-specific tools like local radio stations and mobile phones, but also use language tailored to farmer contexts when disseminating information. Policymakers should leverage on social and cultural settings when designing information interventions.

The study highlights critical factors that significantly promote information use for improved productivity for SHFs, cumulatively increasing the country’s gross domestic product (GDP). Socially, findings may reduce on their poverty levels of farmers.

This study offers a novel perspective in information literacy domain by using the SLT to delineate contextual tools that are paramount in predicting of information literacy in an under research informal context of SHFs.

The purpose of this paper is to predict the machining performance of electrical discharge machining of Ti-13Nb-13Zr (TNZ) alloy, a promising biomedical alloy, using artificial neural networks (ANN) models.

In the research, three major performance characteristics, i.e. the material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR), were chosen for the study. The input parameters for machining were the voltage, current, pulse-on time and pulse-off time. For the ANN model, a two-layer feedforward network with sigmoid hidden neurons and linear output neurons were chosen. Levenberg–Marquardt backpropagation algorithm was used to train the neural networks.

The optimal ANN structure comprises four neurons in input layer, ten neurons in hidden layer and one neuron in the output layer (4–10-1). In predicting MRR, the 60–20-20 data split provides the lowest MSE (0.0021179) and highest R-value for training (0.99976). On the contrary, the 70–15-15 data split results in the best performance in predicting both TWR and SR. The model achieves the lowest MSE and highest R-value for training in predicting TWR as 1.17E-06 and 0.84488, respectively. Increasing the number of hidden neurons of the network further deteriorates the performance. In predicting SR, the authors find the best MSE and R-value as 0.86748 and 0.94024, respectively.

This is a novel approach in performance prediction of electrical discharge machining in terms of new workpiece material (TNZ alloys).

The purpose of this study is to provide the enhancement of power quality of a high power-rated voltage source inverter driven induction motor with a three-phase, three-level neutral point clamped converter placed at the front end, while a passive power filter is connected in shunt with it. The improvement in power quality can be achieved by reducing the total harmonic distortion in source current. The controllers were designed for the linearization of the high-power induction motor drive. A control method is presented for the regulation of the common DC-link voltage.

The induction motor is modeled using its dynamic equations, and a decoupling controller is designed to linearize the nonlinear dynamics of the drive through feedback. The common DC-link voltage of the proposed front-end connected converter is monitored and controlled through a control method which feeds the pulse width modulated inverter that drives the induction motor. A passive power filter is designed to meet the reactive power requirement of the system in addition to improve the power quality.

Simulations were carried out for the proposed topology of the drive mechanism, and the outcomes were analyzed by a comparative analysis of the drive system both in the presence of the passive filter as well as in the absence of the filter. The total harmonic distortion is found to be reduced enough to meet the standards with the designed filter, and the reactive power is also compensated considerably. The input power factor at the supply side is maintained almost to unity, and the DC-link voltage of the proposed circuit topology is maintained at the desired level. The overall performance of the drive system was found to be useful and economical.

A new topology of a front-end connected three-level neutral point clamped converter to a high power-rated induction motor drive is proposed. The drive is fed by a pulse width modulated inverter with a common DC-link with the front end connected converter. A passive filter is designed with respect to the reactive power requirement of the system and connected in shunt to the converter at the supply side. Control schemes are designed and used for the drive system and also for the regulation of the common DC-link voltage of the proposed front end connected converter.