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Non-linear power–voltage characteristics of solar cell and frequently changing output due to variation in solar irradiance caused by movement of clouds are the major issues need to be considered in photovoltaic (PV) penetration to maintain the power quality of the grid. It is important for a PV module to always function at its maximum available power point to increase the efficiency and to maintain the grid stability. A possible solution to mitigate these generation fluctuations is the use of an electric double-layer capacitor or supercapacitor energy storage device, which is an efficient storage device for power smoothing applications. This study aims to propose a power smoothing control approach to smoothen out the output power variations of a solar PV system using a supercapacitor energy storage device.

To extract the maximum possible power from a PV panel, there are several maximum power points tracking (MPPT) algorithms developed in literature. Fuzzy logic controller-MPPT method is used in this work as it is a very efficient and popular technique which responds quickly under varying ecological conditions, reduced computational complexity and does not depend on any system constraints. Fuzzy logic-based MPPT controller by Boost DC–DC converter is developed for operating the PV panels at available maximum power point. Fuzzy logic-proportional integral (PI) charge controller is implemented by Buck–Boost converter to provide the constant current and suitable voltage for supercapacitor and to achieve better power smoothing. PI charge controller is preferred in this work as it offers better outcomes and is very easy to implement.

Simulation results conclude that the proposed power smoothing control approach can efficiently smooth out the power variations under variable irradiance and temperature situations. To confirm the accurateness of the proposed system, it is validated for poly-crystalline PV module and comparison of results is done by using different case study with and without the use of an energy storage system under change in irradiance condition. The proposed system is developed and examined on MATLAB/Simulink environment.

The performance comparison between PV power output with and without the use of a supercapacitor energy storage device under different Case Studies shows that the improved performance in smoothing of power output was achieved with the use of a supercapacitor energy storage device.

Estimation of solar cell parameters, mathematical modeling and the actual performance analysis of photovoltaic (PV) cells at various ecological conditions are very important in the design and analysis of maximum power point trackers and power converters. This study aims to propose the analysis and modeling of a simplified three-diode model based on the manufacturer’s performance data.

A novel technique is presented to evaluate the PV cell constraints and simplify the existing equation using analytical and iterative methods. To examine the current equation, this study focuses on three crucial operational points: open circuit, short circuit and maximum operating points. The number of parameters needed to estimate these built-in models is decreased from nine to five by an effective iteration method, considerably reducing computational requirements.

The proposed model, in contrast to the previous complex nine-parameter three-diode model, simplifies the modeling and analysis process by requiring only five parameters. To ensure the reliability and accuracy of this proposed model, its results were carefully compared with datasheet values under standard test conditions (STC). This model was implemented using MATLAB/Simulink and validated using a polycrystalline solar cell under STC conditions.

The proposed three-diode model clearly outperforms the earlier existing two-diode model in terms of accuracy and performance, especially in lower irradiance settings, according to the results and comparison analysis.

The purpose of this paper is to provide a systematic review of literature on corporate engagement with start-ups (CEWS) by identifying the modes, contexts, antecedents, barriers and outcomes. As an emerging field, CEWS presently has no such review available which will help in building consensus within the field and shape future research directions.

The study followed a two-phased systematic review of literature. Three research databases (i.e. Web of Science, ScienceDirect and SCOPUS) were accessed to gather and conduct the review. Of the total 379 papers retrieved, 63 total relevant papers were studied and analysed. The exhaustive review of literature helped to uncover the contexts, perspectives, antecedents, outcomes and barriers reported across the different modes of CEWS.

The study highlighted the five prominent modes of CEWS favoured by large corporations and start-ups. It found that the large corporations and start-ups associate with one another on the basis of complementarities of activities, resources and motives to pursue their strategic orientations. The engagements also face barriers on the ground, such as incompatibility of goals, power imbalances, cultural differences and weak engagement plans. Most important contexts seen were the high-technology industries in the developed economies like the USA and Europe. It also found that ecosystem creation, accessing innovation and corporate strategy have been preferred as the most productive modes of CEWS in the literature.

This review provides practitioners with a detailed list of the modes and drivers of CEWS. Subsequently, the barriers that need to be managed to successfully execute a specific mode of engagement. This shall enable the practitioners in developing and adopting the best practices while engaging with the start-ups to better facilitate the outcomes of CEWS.

To the best of the authors’ knowledge, there is no systematic literature review available in the domain of CEWS – thus, this study makes an important methodological contribution to the field. By consolidating the fragmented yet growing knowledge on CEWS, the study presents a detailed understanding of what drives and obstructs the engagement between large corporations and start-ups.

This study aims to generate different three-dimensional (3D) foam models using computer tomography (CT) scan and solid continuum techniques. The generated foam models were used to study deformation mechanism and the elastic-plastic behaviour with the existing experimental foam behaviour.

CT scan model was generated by combing 2D images of foam in MIMICS software. Afterwards, it was imported in ABAQUS/CAE software. However, solid continuum model was generated in ABAQUS/CAE software by using crushable foam properties. Then, the generated foam models were sets boundary conditions for a compression test.

CT scans capture the actual morphology of foam sample which may directly an image based finite element foam model. The sectional views of both the models were used to observe deformation mechanism on compression. The real compressive behaviour of foam was visualised in CT-Scan foam model. It was observed that CT-scan model was the more accurate modelling method than crushable foam model.

The internal structure of foam is very complex and difficult to analyse. Therefore, CT-scanning may be the accurate method for capturing the macro-level detailing of foam structure. A CT-scan foam model can be used for multiple times for mechanical analysis using a simulation software, which may reduce the manufacturing and the experimental cost and time.

To overcome the need of seasonal fruit ber, consumers prefer to use fruits in such a form that can be prepared easily or consumed instantly. By transforming them into powders, they can be effortlessly attained as well as preserved, stored and processed.

To optimize the spray drying conditions for development of ber fruit powder, response surface methodology was used. The experimental design consisted of 13 runs. The levels of independent variables, i.e. inlet air temperature, varied from 153.79ºC to 196.21ºC and maltodextrin concentration, from 4.17 to 9.83 per cent. The responses were moisture content, bulk density, solubility, vitamin C, ΔE and L value.

The second-order polynomial model fitted for moisture content, bulk density, solubility, vitamin C, ΔE and L value was highly significant (p < 0.001) for each response. The inlet air temperature showed maximum influence on moisture content, bulk density, solubility and vitamin C, whereas the maltodextrin concentration showed maximum influence on bulk density, solubility, ΔE and L value. The predicted values were attained as moisture 4.90 per cent, bulk density 0.35g/ml, solubility 89.11 per cent, vitamin C 91.06mg/100g, ΔE 31.03 and L 87.78. The recommended optimum spray drying conditions were inlet air temperature and maltodextrin concentration of 166.64°C and 9.26 per cent, respectively.

Spray drying of the underused Indian fruit ber has enhanced its utility. Ber powder can further be used as an instant beverage, in sweets, as a flavoring agent and in soft drinks.

This study aims to examine the combinations of internal and external knowledge flows between research and development (R&D) incumbents and start-ups in the context of open innovation. While there is a growing body of knowledge that has examined how, in a knowledge economy, a firm’s knowledge and innovation activities are closely linked, there is no systematic review available of the key antecedents, perspectives, phenomenon and outcomes of knowledge spillovers.

The authors have conducted dual-stage research. First, the authors conducted a systematic review of literature (97 research articles) by following the theories–contexts–methods framework and the antecedent-phenomenon-outcomes logic. The authors identified the key theories, contexts, methods, antecedents, phenomenon and outcomes of knowledge spillovers between R&D-driven incumbents and start-ups in the open innovation context. In the second stage, the findings of stage one were leveraged to advance a nomological network that depicts the strength of the relationship between the observable constructs that emerged from the review.

The findings demonstrate how knowledge spillovers can help incumbent organisations and start-ups to achieve improved innovation capabilities, R&D capacity, competitive advantage and the creation of knowledge ecosystems leading to improved firm performance. This study has important implications for practitioners and managers – it provides managers with important antecedents of knowledge spillover (knowledge capacities and knowledge types), which directly impact the R&D intensity and digitalisation driving open innovation. The emerging network showed that the antecedents of knowledge spillovers have a direct relationship with the creation of a knowledge ecosystem orchestrated by incumbents and that there is a very strong influence of knowledge capacities and knowledge types on the selection of external knowledge partners/sources.

This study has important implications for practitioners and managers. In particular, it provides managers with important antecedents of knowledge spillover (knowledge capacities and knowledge types), which directly impact the R&D intensity and digitalisation driving open innovation. This will enable managers to take important decisions about what knowledge capacities are required to achieve innovation outcomes. The findings suggest that managers of incumbent firms should be cautious when deciding to invest in knowledge sourcing from external partners. This choice may be driven by the absorptive capacity of the incumbent firm, market competition, protection of intellectual property and public policy supporting innovation and entrepreneurship.

Identification of the key antecedents, phenomenon and outcomes of knowledge spillovers between R&D-driven incumbents and start-ups in the open innovation context. The findings from Stage 1 helped us to advance a nomological network in Stage 2, which identifies the strength and influence of the various observable constructs (identified from the review) on each other. No prior study, to the best of the authors’ knowledge, has advanced a nomological network in the context of knowledge spillovers between R&D-driven incumbents and start-ups in the open innovation context.

This paper aims to probe into the linkages between the corporate social responsibility (CSR) practices of banks and the cross-buying intentions of banking customers. Though the authors could not find any direct link between these two concepts on theoretical ground, but an effort has been made to identify the impact of CSR on cross-buying intentions through corporate reputation and relationship quality. Like other industries, the Indian banking industry has also witnessed a balance between its social-environmental responsibilities and its clearly defined economic responsibility to earn profit.

The universe for the present study constitutes the customers of the entire Indian banking industry. Considering the cost and time constraints, the study was limited to a sample of 347 public and private bank customers in the Rajasthan region based on the convenience sampling method. Data were collected using a structured questionnaire and analyzed through structural equation modeling. CSR measures included philanthropic and ethical responsibility.

Results revealed that corporate reputation and relationship quality both play a mediating role in the linkages between CSR and cross-buying intentions.

The study suggests integrating marketing strategy with its CSR strategies to encourage cross-buying intentions. While making the cross-selling agenda, they should bear reputation in mind because at the relationship development phase, customers generally rely on reputation than their evaluation of bank’s products for cross-buying.

This study is the first in marketing literature which relates the concept of CSR and the cross-buying.