Charu Verma and Pradeep Kumar Suri
The purpose of this paper is to highlight the use of big data through patentometric insights for R&D decision-making.
Abstract
Purpose
The purpose of this paper is to highlight the use of big data through patentometric insights for R&D decision-making.
Design/methodology/approach
This study assesses the inventive activity through ‘big data’ patents, registered by inventors worldwide, using WIPO Patentscope database. The objective is to use the insights from patentometrics for R&D decision-making. The data from WIPO PatentScope (https://patentscope.wipo.int/search/en/search.jsf) was searched for current patent scenario in area of ‘big data’. The data was further organized and cleaned using the Google ‘OpenRefine’. Data was pre-processed to remove all null values. Cleaned data was analyzed using programming language ‘R’, MS Excel (charts and Pivot tables) and free data visualization tool called ‘Tableau Public’, to get insights for R&D decision-making.
Findings
The key insights included trends (patents with years of publication), top technologies trending the current space, top organizations leading in these technologies and the top inventors who are publishing patents in these technologies through leading organizations were drawn. Details in Section 5 in the paper.
Research limitations/implications
Global patent data is multi-lingual and spreads across a set of multiple databases. Domain experts may be required to assess, identify and extract the relevant information for analysis and visualization of multi-lingual distributed data sets. Government organizations generally have multi-dimensional goals that may be more toward societal benefits. On the other hand, the commercial companies are more focused on profit. Therefore, the performance management process has to be really effective because it is critical for getting value in the government sector.
Practical implications
Insights from patent analytics serve as the important input to R&D managers as well as policymakers to assess the global needs to plan the national orientation according to the global market. This will help further for R&D projects prioritization, planning, budget allocations, human capital planning and other gamut of R&D management and decision-making.
Social implications
Facilitation for R&D institutions (government as well as private) to formulate the research strategy for the domains or research areas to delve into. R&D decisions will be completely data-driven making them more accurate, reliable, valid and informed. These insights are very relevant for policymakers as well to facilitate the need assessment to determine the National priorities, make improvements in meeting societal country-level challenges during the resource allocation at top and subsequently at all other levels.
Originality/value
Data analytics of global patents in “big data” till 2019 to get insights to facilitate R&D decision-making.
Details
Keywords
Ashutosh Shankhdhar, Pawan Kumar Verma, Prateek Agrawal, Vishu Madaan and Charu Gupta
The aim of this paper is to explore the brain–computer interface (BCI) as a methodology for generating awareness and increasing reliable use cases of the same so that an…
Abstract
Purpose
The aim of this paper is to explore the brain–computer interface (BCI) as a methodology for generating awareness and increasing reliable use cases of the same so that an individual's quality of life can be enhanced via neuroscience and neural networks, and risk evaluation of certain experiments of BCI can be conducted in a proactive manner.
Design/methodology/approach
This paper puts forward an efficient approach for an existing BCI device, which can enhance the performance of an electroencephalography (EEG) signal classifier in a composite multiclass problem and investigates the effects of sampling rate on feature extraction and multiple channels on the accuracy of a complex multiclass EEG signal. A one-dimensional convolutional neural network architecture is used to further classify and improve the quality of the EEG signals, and other algorithms are applied to test their variability. The paper further also dwells upon the combination of internet of things multimedia technology to be integrated with a customized design BCI network based on a conventionally used system known as the message query telemetry transport.
Findings
At the end of our implementation stage, 98% accuracy was achieved in a binary classification problem of classifying digit and non-digit stimuli, and 36% accuracy was observed in the classification of signals resulting from stimuli of digits 0 to 9.
Originality/value
BCI, also known as the neural-control interface, is a device that helps a user reliably interact with a computer using only his/her brain activity, which is measured usually via EEG. An EEG machine is a quality device used for observing the neural activity and electric signals generated in certain parts of the human brain, which in turn can help us in studying the different core components of the human brain and how it functions to improve the quality of human life in general.
Details
Keywords
Mala Sharma and Pratibha Verma
This research examines and analyzes the impact of employee branding and employer branding in multinationals that exceeded the national boundaries in globalization. The motive of…
Abstract
This research examines and analyzes the impact of employee branding and employer branding in multinationals that exceeded the national boundaries in globalization. The motive of the research is to identify the significance of employer and employee branding for the success of the multinationals. The emergence of a MNC culture in India is widespread, and it promotes an employee-oriented philosophy by making all the amenities available to the employees. Multinational organizations focus on employee and employer branding to achieve the desired goals. Employee branding is a new term in the service industry that emphasizes the internal marketing of the organization Infront towards the external image of a company. India has a significant presence of service sectors as in the top 10 around the world. Employment rate in the service sector in India is more that 32.33% as per the collected data by the World Bank in 2020, wherein the large number of employees contributing their services in the different fields becomes a matter of concern for a company’s policies. This research was conducted on a population sample size of 204 respondents working in multinational organizations of Gurugram, India, using convenience sampling through a structured questionnaire. Data analysis of the survey was coded in Ms-excel 2015 and SPSS-21. Primary and secondary data are used in this study. Primary data are collected through questionnaire method, and secondary data are collected through journals, books, websites etc. This study will help human resource managers to improve HR policies and organization culture and to increase employee branding to gain desired success in organizations.
Details
Keywords
Shivam Gupta, Sameer Kumar, Sanjay Kumar Singh, Cyril Foropon and Charu Chandra
Cloud-based enterprise resource planning (ERP) enables an organization to pay for the services they need and removes the need to maintain information technology infrastructure…
Abstract
Purpose
Cloud-based enterprise resource planning (ERP) enables an organization to pay for the services they need and removes the need to maintain information technology infrastructure. The purpose of this paper is to empirically test the role of cloud-based ERP services on the performance of an organization. Here, the performance is categorized as supply chain performance and organizational performance that comprises of financial performance and marketing performance. Contingent resource-based view (RBV) theory was used to develop a theoretical framework in which supply base complexity (SBC) acts as a moderating variable on the relationship between cloud ERP and the performance.
Design/methodology/approach
Contingent RBV theory is used to explain the relationship between all identified variables in this paper. Partial least squares (PLS) based on structural equation modeling (SEM) is used to empirically test our theoretical framework.
Findings
The PLS-SEM analysis of 154 respondents supports the contingent RBV theory. Six hypotheses – out of the eight hypotheses formulated in this paper – are supported by data.
Research limitations/implications
Given this study was conducted in India where the potential of cloud ERP has not been fully implemented yet, the results may reflect more of perceived usefulness of this technology. The authors have attempted to understand the effect of SBC as a moderator in the relationship between cloud ERP and organizational performance which may not be the only moderator affecting this relationship among other potential moderators.
Originality/value
This paper empirically validates the theoretical framework based on the contingent RBV theory as it mitigates the static nature of the resource-based view approach suggested in the seminal article of Barney (1991).
Details
Keywords
Sameer Kumar, Bharti Ramtiyal, Gunjan Soni, Lokesh Vijayvargy, Charu Chandra and Ishaan Dey
Traceability is predicted to usher in a fundamental shift in the way transactions in supply chains (SCs) are carried out. By reducing the negative aspects of trust-related issues…
Abstract
Purpose
Traceability is predicted to usher in a fundamental shift in the way transactions in supply chains (SCs) are carried out. By reducing the negative aspects of trust-related issues in a SC, traceability enables improved visibility and transparency.
Design/methodology/approach
We advance research on traceability adoption in the perishable products supply chain by developing and validating an integrated model that combines the technology acceptance model (TAM), the technology readiness index (TRI) and the theory of planned behavior (TPB). A quantitative approach was employed, collecting data through an online survey of 174 supply chain professionals in major Indian cities using a five-point Likert scale. Participants were selected via LinkedIn, each with at least two years of SCM experience. Nonresponse bias was assessed by comparing early and late respondents, revealing no significant differences. Structural equation modeling (SEM) was used to test various research hypotheses derived from literature. Composite reliability and discriminant validity of constructs were verified before examining the relationships among the constructs within the structural model.
Findings
The study found that the TRI components of optimism and innovation did not impact perceived ease of use or perceived utility. Additionally, behavioral intention is shaped by perceived utility, attitude and perceived behavioral control.
Practical implications
This research provides valuable insights for managers aiming to adopt traceability in supply chains (SCs). It helps identify critical factors for effective traceability adoption, showing that perceived ease of use (PEU) and perceived usefulness are pivotal in shaping practitioners’ intentions. Managers should prioritize developing intuitive, user-friendly traceability applications that demonstrate clear value in optimizing SC efficiency. The study also reveals that while practitioners are generally optimistic about traceability, they may feel indifferent or lack a sense of control over it. Therefore, companies should focus on marketing strategies that empower decision-makers, highlighting the ease of use and practical benefits of traceability. Additionally, the findings suggest that perceived behavioral control, combined with intention, can effectively predict traceability adoption. By understanding these dynamics, managers can better guide their firms in successfully implementing traceability, ensuring both technological acceptance and operational efficiency.
Originality/value
This research offers a novel and in-depth exploration of traceability as an emerging concept in supply chains, particularly in India, where adoption remains limited. It highlights that while SC practitioners recognize traceability’s potential, they lack practical expertise, often driven by curiosity about decentralized databases. It underscores the critical role of artificial intelligence, IoT devices and big data in ensuring precise data collection and analytics, essential for successful traceability. The research also introduces a predictive model combining TAM, TRI and TPB constructs, identifying perceived usefulness, attitude and perceived behavioral control as key factors influencing traceability adoption.
Details
Keywords
Anjali Dutta and Santosh Rangnekar
This study aims to investigate the relationship between individuals' preference for teamwork and communities of practice (CoPs) mediated by individuals' concern for team members…
Abstract
This study aims to investigate the relationship between individuals' preference for teamwork and communities of practice (CoPs) mediated by individuals' concern for team members built from the perspective of social learning system for knowledge sharing and learning. A cross-sectional study with data collected from the respondents through a convenience, non-random, non-probability sampling technique was employed in this research. The data of 240 were collected from the respondents belonging to manufacturing and service organizations in India and analyzed through confirmatory factor analysis, multiple regression analysis and PROCESS macro from Hayes with bootstrapping technique. The findings from the analysis showed a positive relationship between individuals' preference for teamwork and CoPs, while concern for team members mediated the relationship between preference for teamwork and CoPs. When employees prefer to work in teams, they positively consider participating in CoPs. Thus, organizations should strategically formulate conditions for employees to enable them to prefer working in teams and groups so that they collaborate as CoPs for knowledge creation, sharing and learning. Such learning through CoPs can pave the way for skill development and high-quality performance, thereby evolving as a framework for human capital development. This chapter provides an understanding of the relationship between individual employees' preference for teamwork and CoPs, mediated by individuals' concern for team members in an Indian context. Implications for theory and practice are discussed, along with limitations and future research direction.
Details
Keywords
Charu Goyal and Manoj Patwardhan
The purpose of this paper is to examine the relationship between the individual high-performance human resource practices (HPHRPs) and work engagement (WE) among the employees in…
Abstract
Purpose
The purpose of this paper is to examine the relationship between the individual high-performance human resource practices (HPHRPs) and work engagement (WE) among the employees in the service industry in India.
Design/methodology/approach
The data were collected from a sample of 234 employees working in the service sector in India with the help of a survey questionnaire method. Confirmatory factor analysis was used to validate the data. To test the hypothesized relationship, structural equation modelling was used.
Findings
The results revealed that five HPHRPs have a positive impact on the WE of employees in the service sector in India. Internal career opportunities negatively impact WE.
Research limitations/implications
The study sample is limited to the service sector in India. Researchers are encouraged to study employee and organizational performance measures other than WE which could be impacted by high-performance work practices.
Practical implications
Managers seeking to strengthen WE could implement these HPHRPs in their firms operating in Indian service sector.
Originality/value
The paper is an attempt to provide empirical evidence on how the individual HPHRPs impacts WE in an organization. Earlier research has shown the impact of bundled HPHRPs on WE. Thus, this study is first to empirically test the direct relationship of individual HPHRPs with WE.
Details
Keywords
Diya Sharma, Renu Ghosh, Charu Shri and Divya Khatter
Cryptocurrency, an emerging asset class, is a virtual form of currency that uses cryptography for security and operates on decentralised networks based on blockchain technology…
Abstract
Purpose
Cryptocurrency, an emerging asset class, is a virtual form of currency that uses cryptography for security and operates on decentralised networks based on blockchain technology. It offers both challenges and opportunities for investors, particularly in terms of diversification, risk management and potential returns. Considering this, the present study attempts to investigate the sentimental factors influencing cryptocurrency while unravelling the intricate interplay among these factors.
Design/methodology/approach
To achieve this, interpretive structure modelling (ISM) identifies the hierarchical model of critical sentimental factors, while Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) explores their dependency and driving power. Analytic hierarchy process (AHP) is adopted to rank the drivers.
Findings
Findings reveal that the pandemic, war, religiosity and economic uncertainty are top-level factors dominantly shaping cryptocurrency trends. Simultaneously, Google Search Trends and Herding emerge as the most dependent factors, influenced by sentiments that emerged from other factors.
Practical implications
The study unpacks implications, acknowledges limitations and proposes avenues for future research.
Originality/value
By exploring the interactive interrelationships among identified sentimental factors through ISM-MICMAC analysis and ranking via the AHP, this paper will have a great influence while contributing towards this evolving field.
Details
Keywords
Uday Salunkhe, Bharath Rajan and V. Kumar
Global crises create an environment that is characterized by a fight for survival by countries, companies and citizens. While firms have adopted business initiatives to ensure…
Abstract
Purpose
Global crises create an environment that is characterized by a fight for survival by countries, companies and citizens. While firms have adopted business initiatives to ensure survival in a global crisis, many measures are geared toward preventing customer churn, declining revenues and eroding market share. Such short-term focus raises an important question regarding long-term survival – how can firms survive a global crisis? The purpose of this study is to investigate how firms can survive a global crisis.
Design/methodology/approach
This study considers pandemics as the study context and uses a triangulation methodology (past research, managerial insights and popular press articles) to advance the organizing framework. Using the process study approach, the proposed framework recognizes the onset characteristics of a global crisis with a focus on pandemics and the government actions that reflect the pandemic onset. The framework also identifies a logical order of three marketplace reactions to the pandemic – management response, consumer response and critical business transformations that ultimately lead to firm survival – and advances related research propositions of such reactions.
Findings
By deploying critical business transformations, firms can ensure firm survival in a pandemic by fostering engagement with customers, employees and resources. Additionally, the moderators that influence the relationships between (1) management response and critical business transformations, (2) consumer response and critical business transformations, and (3) critical business transformations and firm survival are identified. Finally, this study presents an agenda for future research.
Research limitations/implications
To the authors' best knowledge, this is the first study to adopt an interdisciplinary approach to study firm survival in a global crisis such as a pandemic. This study answers the call for more research to the growing field of pandemic research in the areas of marketing research and marketing strategy.
Practical implications
The learnings from this study can help firms on what to anticipate and how to respond in a crisis such as a pandemic.
Social implications
Societal welfare is accounted for as firms plan to deal with a crisis.
Originality/value
This is the first study to propose a strategic framework to deal with a crisis that is largely unanticipated where the duration and the impact is not predictable.