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The purpose of this paper is to conceptualize the influencing characteristics of user-generated content over perceived structure of social platforms to plan various business practices to improve the social commerce activities especially in emerging markets.

In first step, key factors are identified from the systematic literature studies and experts’ opinion. Second, total interpretive structural modeling is used to interpret the complexity of relationships among various factors. Further, fuzzy-MICMAC analysis is used to determine the most driving factors to improve the social commerce.

The study illustrates hierarchical relationships that can help policy designers, business leaders and decision makers to gain maximum benefits of mining the user-generated content to implement the people-oriented changes to improve economic capability of a country.

The applicability of the study findings can be deployed mostly in emerging economies. The study has not considered the data security, cyberbullying, authenticity and reliability of shared content spread virally over social sites.

The paper will assist policy makers, business planners and solution providers to give importance to public-led influencing patterns to offer business solutions based on people demand and choices.

The customers’ engagement, sharing reviews, getting suggestions from other people and finding new trends through user-generated content would enable higher social commerce activities.

The paper develops hierarchical relationships to represent the advancements in business and marketing activities based on influencing patterns and behavior of users over social sites.

This paper aims to identify the key factors to design efficient, healthy and potentially economical neighbourhood places in the surroundings of smart cities to reduce the urban polarization for the sustainable urban development.

A two-stage methodology is followed. First, the key factors for neighbourhood are identified from literature studies. The selected factors are validated by sample t-tests. Second, the total interpretive structural modeling is used to interpret the complexity of relationships among various factors. Further, cross-impact matrix multiplication is applied for classification analysis to find the most driving factors for neighbourhood design.

The contribution of this research is to show hierarchical relationships among the various factors to design the neighbourhood places as smart from the perspectives of city planners and decision makers.

The applicability of the research findings is limited to developing countries mainly where population is large and most of cities have high pressure on its infrastructure to fulfil the citizens’ demands.

This paper will aid policymakers, city planners and government officials to design a sustainable smart city model in which smart neighbourhood would also be the potential solution to decrease pressure on a city’s critical infrastructure especially in developing countries.

A smart city could be considered as the centre point of smart initiatives to develop a place smart, and it should continue beyond the city boundaries to enhance the facilities, services, resources utilization and working environment in neighbourhood places also.

The study explores the various literature on neighbourhood planning and then link with smart city development as current need of urban development scenario. The authors propose a hierarchical relation framework to develop the neighbourhood places as smart places to meet the future demand of urbanization in developing countries like India.

Ankle–foot orthoses (AFOs) are assistive devices prescribed for a number of physical and neurological disorders affecting the mobility of the lower limbs. Additive manufacturing has been explored as an alternative process; however, it has proved to be inefficient cost-wise. This work aims to explore the possibilities of generating modular AFO elements, namely, calf, shank and footplate, with the localized composite reinforcement that aids in the optimization of the device in terms of functionality, aesthetics, rigidity and cost.

The conventional lower leg–foot orthosis configuration depends on thermoforming a polymer sheet around a mortar cast with a trademark firmness relying upon the trim-line with the inalienable plan restrictions. In manufacturing of AFO the expert, i.e. orthotist's, guidance is used. Polypropylene and polyethylene material is used in fabrication of AFO to complete all-round reported points of interest over the ordinary outlines, yet their mechanical conduct under administration conditions cannot be effectively anticipated.

AFOs made of polypropylene and polyethylene material are available in the market, which are used by children of age 3-5 years. With the existing AFO design, patients are facing excessive heating and sweating problems during long-term usage. After feedback from patients and orthotists (who prescribed AFO to patients), an attempt has been made to solve the problem with a new and improved AFO design of AFO by using finite element modelling and stress analysis. Also, the results indicate that the new design is similar to the actual product design.

This work introduces the low-cost 3D printing with reinforcement approach as an alternative route for the designing and manufacturing of orthotic devices with complex shapes. It is expected that new applications add-up to increase the body of knowledge about the behaviour of such products which will mix both areas, composite theory and additive manufacturing. This study investigated the fields related to 3D scanning, 3D printing and computer-aided designing for the manufacturing of a customized AFO.

The purpose of this study is improvement of human gait by customized design of ankle foot orthosis (AFO). An has been the most frequently used orthosis in children with cerebral palsy. AFOs are designed to boost existing features or to avoid depression or traumatize muscle contractures. The advantages of AFO’s utilized for advancement in human walk attributes for the improvement in foot deformities patients or youngsters with spastic loss of motion. In this research on the customized design of AFO's to improve gait, there are limitations during walking of foot drop patients. In children with foot drops, specific AFOs were explicitly altered to improve parity and strength which are beneficial to walking positions.

This study proposes the customized design of AFOs using computerized and additive manufacturing for producing advances to alter the design and increase comfort for foot drop patients. Structuring the proposed design fabricated by using additive manufacturing and restricted material, the investigation was finalized at the Design Analysis Software (ANSYS). The system that performs best under investigation can additionally be printed using additive manufacturing.

The results show that the customized design of AFOs meets the patient’s requirements and could also be an alternative solution to the existing AFO design. The biomechanical consequences and mechanical properties of additive manufactured AFOs have been comparable to historically synthetic AFOs. While developing the novel AFO designs, the use of 3D printing has many benefits, including stiffness and weight optimization, to improve biomechanical function and comfort. To defeat the issues of foot drop patients, a customized AFO is used to improve the human gait cycle with new material and having better mechanical properties.

This research work focuses on the biomechanical impacts and mechanical properties of customized 3D-printed AFOs and compares them to traditionally made AFOs. Customized AFO design using 3D printing has numerous potential advantages, including new material with lightweight advancement, to improve biomechanical function and comfort. Normally, new applications mean an incremental collection of learning approximately the behavior of such gadgets and blending the new design, composite speculation and delivered substance production. The test results aim to overcome the new AFO structure issues and display the limited components and stress examination. The outcome of the research is the improved gait cycle of foot drop patients.

The purpose of the study is to examine the value-based performance of firms in construction sector in India using Tobin's Q and Market Capitalization (MCAP) and then determine their significant financial drivers.

The study is based on data from 87 firms engaged in infrastructure, real estate, industrial construction and allied areas in India over a study period of 10 years. Three distinct forms of panel regression models have been developed using Tobin's Q and MCAP as dependent variables. The models developed are using Baltagi's (1981) Error Component 2SLS, Varadharajan-Krishnakumar's (1987) Generalized 2SLS and Arellano – Bower/Blundell – Bond's (1991) dynamic panel.

The study found that MCAP is a better suited value-based performance measure for construction sector firms in India. The study further reports that the age of the firm, profit after tax, investment in research and development, dividends, leverage and net fixed asset are significant positive drivers, whereas cash flow is a significant negative driver.

The study is limited to a geographic location; therefore, the findings of this study cannot be generalized.

As MCAP is a better suited value-based performance measure of a firm in the construction sector, managers should focus on improving profitability, higher research and development activities, higher dividends and higher expenditures on net fixed assets for improvement.

This is an original attempt to examine the value-based performance of firms in the construction sector in India using Tobin's Q and MCAP.

The purpose of this paper is to identify and build a hierarchy of the factors influencing competitiveness of electronics manufacturing industry (EMI) at the industry level and apply the interpretive structural modeling, fuzzy Matriced’ Impacts Croisés Multiplication Appliquée á UN Classement (i.e. the cross-impact matrix multiplication applied to classification; MICMAC) and analytic hierarchy process (AHP) approaches. These factors have been explained with respect to managerial and government policymakers’ standpoint in Indian context.

This study presents a hierarchy and weight-based model that demonstrates mutual relationships among the significant factors of competitiveness of the Indian EMI.

This study covers a wide variety of factors that form the bedrock of the competitiveness of the EMI. Interpretive structural modeling and fuzzy MICMAC are used to cluster the influential factors of competitiveness considering the driving and dependence power. AHP is used to rank the factors on the basis of weights. Results show that the “government role” and “foreign exchange market” have a significantly high driving power. On the other hand, the “capital resource availability” and “productivity measures” come at the top of the interpretive structural modeling hierarchy, implying high dependence power.

The study has strong practical implications for both the manufacturers and the policymakers. The manufacturers need to focus on the factors of competitiveness to improve performance, and at the same time, the government should come forward to build a suitable environment for business in light of the huge demand and frame suitable policies.

The lackluster performance of the industry is because of the existing electronics policies and environmental conditions. The proposed interpretive structural modeling and fuzzy MICMAC and AHP frameworks suggest a better understanding of the key factors and their mutual relationship to analyze competitiveness of the electronics manufacturing industry in view of the Indian Government’s “Make in India” initiatives.

This paper contributes to the industry level competitiveness and dynamics of multi-factors approach and utilize the ISM–fuzzy MICMAC and AHP management decision tool in the identification and ranking of factors that influence the competitiveness of the EMI in the country.

Research assessment has long been important for directing research funding, rationalizing research organizations and enhancing productivity, including concentrating on specialized subjects. But due to a lack of data, research assessment procedures centered on simple indicators that solely included publications and their citation counts. The Dimensions is one such prodigy of technological evolution like the internet in discovering the research data metrics.

This paper outlines Dimensions, the emergence of Dimensions by partnering with various development partners into a single robust platform and provides directions on implementing a free tool for research insights: Dimensions badge.

The Dimensions platform for research insights pulls together data on financing, publications, policy, patents and grants.

This tool is freely available to libraries worldwide.

As the storage and processing requirement of digital information is increasing on the cloud, it is very difficult for the single cloud provider (CP) to meet the resource requirement. Multiple providers form a federation for the execution of users’ requests. For the federated cloud, this paper aims to address the issue distribution of users’ request for resources and revenue among the providers by offering fair and stable distribution models for the federated cloud.

This paper uses cooperative game (CG)-theoretical models, i.e. Shapley–Shubik power index (SSPI) and Banzhaf power index (BPI) for distribution. Performance is analysed using variance and monotonicity using a case study.

Numerical analysis is done using two scenarios. Monotonicity is evaluated. Results show that SSPI performs better as compared to BPI in terms of fairness accuracy and the framework provide the fair distribution of revenue among providers in the federated cloud.

The proposed framework works efficiently under the specific defined conditions.

Paper provides the fair distribution. It assist the centralised cloud exchange in managing the users’ request in such a way every CPs, in the federated cloud will get an equal chance of serving the users’ request. The framework also provides the stable federation. Proposed work provides less rejection rate of users’ request. Finally, it assists the providers in increasing their profits in the federation.

This paper presents a CG theoretic-based framework for the distribution of resources required and revenue. The framework analysed the performance of distribution models by considering the variance and monotonicity for multiple users’ requests.

Amidst the ambiguity about the impact of augmented reality (AR) attributes on hedonic or utilitarian values, the present study aims to understand what AR attributes create hedonic and utilitarian values and how their interaction determines consumers' behavioral intention.

The study synthesizes the results of 19 quantitative studies on AR marketing by using the meta-analysis technique.

The findings reveal that interactivity and augmentation are salient AR attributes that offer users both hedonic and utilitarian values. They are instrumental in fostering users' behavioral intention. However, interactivity does not have any direct influence on the behavioral intentions.

Being one of the first meta-analyses on AR marketing; theoretically, it synthesizes the statistical data of the state of art literature on AR marketing. The results of the study would allow AR practitioners to decide on their AR marketing related activities in a better way.

This paper aims to examine the determinants of the dividend policy of the construction companies in India.

Data from 2011 to 2016 (six years) of 45 listed construction companies in India are collected, and a strong balanced panel is created. Dividend per share is dependent variable, and profitability, unstable earnings, institutional holding, cash flow, tangibility, liquidity, growth opportunities, age of the firm, life cycle, leverage, size of firm and taxation are explanatory variables. The panel is tested for stationarity and finally fixed and random-effect panel regression model with robust estimation option is performed.

The random effect model is found fit with an R² of 62 per cent, and profitability, life cycle and size of the firm show a significant positive effect on dividend payment. Cash flow shows a negative significant relationship, indicating the presence of agency problem. Rest of the variables indicated an insignificant relationship.

The study is carried out on a small sample of 45 companies with data of only six years. Further, there may be behavioral and psychological factors that drive the decision to declare dividend. Those factors have not been considered in present study. Despite considerable efforts, the author could not find more studies specific to the construction sector. Hence, the variables identified in the present study are more generic, even though a few sector-specific studies have been included.

The dividend policy determinants for the construction sector in India are investigated, and a comprehensive model based on 12 explanatory variables is tested to find the drivers of dividend payout in Indian construction companies. From the investor’s point of view, the sector has immense potential in terms of dividend as well as capital appreciation. Therefore, the study can be useful to the investors to understand the drivers of dividend payout in the construction sector. It can also be crucial for companies to create an appropriate dividend policy so as to attract and retain investors. The study contributes significantly to the existing body of knowledge by recommending the salient drivers of dividend payout in the construction sector based on a comprehensive dataset and using robust methodology.