Search results

The privacy of the information is a major challenge in the communication process. In the present modern generation, the cryptography plays a vital role in providing security for data, such as text, images and video while transmitting from source to destination through internet or intranet. The Rivest-Shamir-Adleman (RSA) is an asymmetric key cryptographic system, where the security of the method works on the strength of the key.

In an asymmetric key crypto system, a pair of keys is generated one public key for encryption and one private key for decryption. The major challenge of implementing the RSA is the power function which becomes tedious and time consuming as the exponential value increases. The Chinese remainder theorem proves to be the best for data encryption when it comes to execution time of the algorithm. The proposed novel RSA algorithm with lookup table (LUT) is an extension to the Chinese remainder algorithm, which works better for image and video in terms of time complexity.

This paper presents a LUT approach for implementing the RSA with a minimal processing time. The proposed algorithm was compared with the standard algorithms like, Chinese remainder theorem, binary approach and squared multiplication approach. As the size of the exponent value increases, the proposed method shows better performance compared to other standard methods.

This paper presents a LUT approach for implementing the RSA with a minimal processing time. The proposed algorithm was compared with the standard algorithms like, Chinese remainder theorem, binary approach and squared multiplication approach. As the size of the exponent value increases, the proposed method shows better performance compared to other standard methods.

Land value varies at a micro level depending on the location’s economic, geographical and political determinants. The purpose of this study is to present a comprehensive assessment of the determinants affecting land value in the Indian city of Thiruvananthapuram in the state of Kerala.

The global influence of the identified 20 explanatory variables on land value is measured using the traditional hedonic price modeling approach. The localized spatial variations of the influencing parameters are examined using the non-parametric regression method, geographically weighted regression. This study used advertised land value prices collected from Web sources and screened through field surveys.

Global regression results indicate that access to transportation facilities, commercial establishments, crime sources, wetland classification and disaster history has the strongest influence on land value in the study area. Local regression results demonstrate that the factors influencing land value are not stationary in the study area. Most variables have a different influence in Kazhakootam and the residential areas than in the central business district region.

This study confirms findings from previous studies and provides additional evidence in the spatial dynamics of land value creation. It is to be noted that advanced modeling approaches used in the research have not received much attention in Indian property valuation studies. The outcomes of this study have important implications for the property value fixation of urban Kerala. The regional variation of land value within an urban agglomeration shows the need for a localized method for land value calculation.

Property tax continues to be the most viable, steady, progressive and genuine source of income for an independent local government administration in India. Kerala has one of the most complex cadastral and property taxation systems in the country. In 2008, the Kerala government introduced “Fair value of land” for all landed property in Kerala, which is calculated per Are and notified by the Government of Kerala on the website. This paper presents the outcome of the spatial mapping of the fair value of land in Kerala and its comparison with actual land value collected through advertisements and surveys.

The methodology used in this study analyzed the existing fair value system of land valuation in Kerala and identified its drawbacks. Fair value is integrated into cadastral data in geographical information system (GIS) and spatially analyzed to identify the discrepancies in fair value fixation. The actual land value for 837 locations is collected from online advertisements and verified through a field survey. A paired t-test analysis follows this to compare the fair value and actual land value of the study area.

The disparity between the original land value and the registration value in Kerala has resulted in the undervaluation of land resources by the government. The fair value fixed by the government is significantly lower than the actual land value based on the statistical comparison results. It is observed that the actual land value is multiple times higher than the government fixed land value. Also, the spatial distribution of the village level fair value shows the randomness in fixation and abnormalities existing at numerous locations.

The results indicate that the traditional comparison method used for fair value calculation by the Kerala government is not suitable in Indian scenarios due to the unreliability of registration values. The study thus points to the importance of developing a scientific method for determining the land value that would consider various spatially influencing parameters.

The current study provided an in-depth analysis of the land valuation system of the Kerala government. The strengths and weaknesses of the existing system are analyzed through statistical methods.

Real estate valuation studies gained popularity with the availability of large-scale property transaction data in the latter part of the twentieth century. Hedonic price modeling (HPM) was the most popular method in the initial years until it was taken over by advanced modeling methods in the twenty-first century. Even though there exist a few literature reviews on this topic, no comprehensive bibliometric analysis is conducted in this area. In view of gaining a better understanding of the dynamics of property valuation studies, this paper aims to conduct a bibliometric analysis.

A comprehensive search in the Scopus database, followed by detailed screening resulted in 1,400 articles. The identified research articles spanning over five decades (1964–2019) are analyzed using the open-source R package “bibliometrix.”

The study found the USA to be the most productive country in various aspects, such as number of publications, number of authors and publication hotspots. The findings also demonstrate assessments on the publication trends, journals, citations, keywords, co-citation and collaboration networks. It was observed that there exists an upsurge in the number of publications after the year 2000 owing to improved data availability and better modeling techniques.

This study is significant in understanding the major research areas and modeling techniques used in property valuation. Future studies can incorporate multiple database sources and include more articles.

The current study is one of the first bibliometric studies on property valuation. Previous studies have not explored the possibilities of geographic information system in bibliometric research. Spatial mapping and analysis of publications provide a geographical perspective of valuation research.

Journal of Corporate Real Estate (JCRE) is an international journal of repute. JCRE is an interdisciplinary journal focusing on corporate real estate management and caters to the needs of real estate owners and end-users. The journal's scope includes private and public sector corporate real estate owned and used by businesses to run their operations. This paper aims to analyze the journal's impact using bibliometric analysis from 1998 to 2017 on 380 publications.

The network analysis is performed using VOSviewer software and Biblioshiny R studio. The mapping presents citation structures, coauthorship patterns, bibliographic coupling and other network analyses.

The results show that the journal is growing in terms of citations and impact. The findings document various mapping criteria and their summaries. Seven major clusters are identified to delineate the underlying themes of publications in JCRE.

To the best of the authors’ knowledge, this paper offers the original and first bibliometric analysis of the journal’s impact over the first two decades. The findings are relevant for researchers and real estate stakeholders.

Equipment performance helps the manufacturing sector achieve operational and financial improvements despite process variations. However, the literature lacks a clear index or metric to quantify the monetary advantages of enhanced equipment performance. Thus, the paper presents two innovative monetary performance measures to estimate the financial advantages of enhancing equipment performance by isolating the effect of manufacturing fluctuations such as product mix price, direct and indirect characteristics, and cost changes.

The research provides two measures, ISB (Improvement Saving Benefits) and IEB (Improvement Earning Benefits), to assess equipment performance improvements. The effectiveness of the metrics is validated through a three stages approach, namely (1) experts' binary opinion, (2) sample, and (3) actual cases. The relevant data may be collected through accounting systems, purpose-built software, or electronic spreadsheets.

The findings suggest that both measures provide an effective cost–benefit analysis of equipment performance enhancement. The measure ISB indicates savings from performance increases when equipment capacity is greater than product demand. IEB is utilised when equipment capacity is less than product demand. Both measurements may replace the unitary cost variation, which is subject to manufacturing changes.

Manufacturing businesses may utilise the ISB and IEB metrics to conduct a systematic analysis of equipment performance and to appreciate the financial savings perspective in order to emphasise profitability in the short and long term.

The study introduces two novel financial equipment performance improvement indicators that distinguish the effects of manufacturing variations. Manufacturing variations cause cost advantages from operational improvements to be misrepresented. There is currently no approach for manufacturing organisations to calculate the financial advantages of enhancing equipment performance while isolating production irregularities.

The purpose of this paper is to examine the development of rice supply chain in the context of the role of rice farmer organizations and cooperative networks in Thailand.

Primary data were solicited from the cooperatives and members of cooperatives for this study through questionnaire administration. The questionnaire containing a five-point Likert scale was posed to respondents to ascertain their problems before and after joining the network (for cooperative) and after joining the cooperative (for members). This study employed the independent two-sample student t-test (two-tailed) to test for significant difference in the means of scores regarding the problems of cooperatives before and after the cooperative network, and also to test for significant difference in the means of scores of the problems of members of the cooperatives before and after joining the cooperative.

The study revealed that key production and marketing problems such as increased transaction costs and market uncertainties confronting the cooperative organizations have been diminished as a result of the networks. Key problems of the members of the cooperatives such as exploitation and opportunistic behavior of traders to whom they sell their products have been reduced as a result of joining the cooperatives.

This paper is not without caveat. The governance structures in relation to leadership, financial arrangements and bargaining power balance have not been analyzed in this study and these are avenues for further research.

To the best of the authors’ knowledge, this study is the first that examined the combined roles of farmer organizations and cooperative networks in developing the rice supply chain in Thailand.

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 purpose of this paper is to investigate the effects of irregular unsettling on the smoking model in form of the stochastic model as in the deterministic model these effects are neglected for simplicity.

In this research, the authors investigate a stochastic smoking system in which the contact rate is perturbed by Lévy noise to control the trend of smoking. First, present the formulation of the stochastic model and study the dynamics of the deterministic model. Then the global positive solution of the stochastic system is discussed. Further, extinction and the persistence of the proposed system are presented on the base of the reproductive number.

The authors discuss the dynamics of the deterministic smoking model form and further present the existence and uniqueness of non-negative global solutions for the stochastic system. Some previous study’s mentioned in the Introduction can be improved with the help of obtaining results, graphically present in this manuscript. In this regard, the authors present the sufficient conditions for the extinction of smoking for reproductive number is less than 1.

In this work, the authors investigated the dynamic stochastic smoking model with non-Gaussian noise. The authors discussed the dynamics of the deterministic smoking model form and further showed for the stochastic system the existence and uniqueness of the non-negative global solution. Some previous study’s mentioned in the Introduction can be improved with the help of obtained results, clearly shown graphically in this manuscript. In this regard, the authors presented the sufficient conditions for the extinction of smoking, if <1, which can help in the control of smoking. Motivated from this research soon, the authors will extent the results to propose new mathematical models for the smoking epidemic in the form of fractional stochastic modeling. Especially, will investigate the effective strategies for control smoking throughout the world.

This study is helpful in the control of smoking throughout the world.

Artificial intelligence (AI) is increasingly applied by businesses to optimize their processes and decision-making, develop effective and efficient strategies, and positively influence customer behaviors. Businesses use AI to generate behaviors such as customer retention (CR). The existing literature on “AI and CR” is vastly scattered. The paper aims to review the present research on AI in CR systematically and suggest future research directions to further develop the field.

The Scopus database is used to collect the data for systematic review and bibliometric analysis using the VOSviewer tool. The paper performs the following analysis: (1) year-wise publications and citations, (2) co-authorship analysis of authors, countries, and affiliations, (3) citation analysis of articles and journals, (4) co-occurrence visualization of binding terms, and (5) bibliographic coupling of articles.

Five research themes are identified, namely, (1) AI and customer churn prediction in CR, (2) AI and customer service experience in CR, (3) AI and customer sentiment analysis in CR, (4) AI and customer (big data) analytics in CR, and (5) AI privacy and ethical concerns in CR. Based on the research themes, fifteen future research objectives and a future research framework are suggested.

The paper has important implications for researchers and managers as it reveals vital insights into the latest trends and paths in AI-CR research and practices. It focuses on privacy and ethical issues of AI; hence, it will help the government develop policies for sustainable AI adoption for CR.

To the author's best knowledge, this paper is the first attempt to comprehensively review the existing research on “AI and CR” using bibliometric analysis.