Ankesh Mittal

Bio: Ankesh Mittal is an academic researcher from Sant Longowal Institute of Engineering and Technology. The author has contributed to research in topics: Business & Total quality management. The author has an hindex of 2, co-authored 7 publications receiving 16 citations.

Addressing strategic human resource management practices for TQM: the case of an Indian tire manufacturing company

Abstract: PurposeThis study aims to identify SHRM (strategic human resource management) essential practices for the TQM (total quality management) program regarding an Indian tire manufacturing company and formulate an inclusive interrelationship to prioritize them.Design/methodology/approachSemistructured interview with ten experts from the company was made to give SHRM practices scores. The SLR (systematic literature review) and TOPSIS (technique for order of preference by similarity to ideal solution) techniques are used to establish the model for 12 key practices and rank them afterward.FindingsThe findings clearly show that strategic planning and staffing, teamwork and leadership development have appeared as the top three essential practices. Simultaneously, performance measurement and evaluation, work design and analysis and promotion are identified as the bottom three practices. These essential practices are identified as contributing attributes.Practical implicationsThe findings prioritize the SHRM practices as contributing attributes that help other tire manufacturing industries identify their key practices. Moreover, it provides the necessary inputs comprised of ten experts' decisions to become more active and well prepared.Originality/valueThe novelty of this study is to identify the key practices by using SLR and measured by the TOPSIS method to rank and consider a tire manufacturing company as a case-based approach to gain high productivity and competitive advantage.

The role of 3S in big data quality: a perspective on operational performance indicators using an integrated approach

Abstract: PurposeThis study aims to provide insight into the operational factors of big data. The operational indicators/factors are categorized into three functional parts, namely synthesis, speed and significance. Based on these factors, the organization enhances its big data analytics (BDA) performance followed by the selection of data quality dimensions to any organization's success.Design/methodology/approachA fuzzy analytic hierarchy process (AHP) based research methodology has been proposed and utilized to assign the criterion weights and to prioritize the identified speed, synthesis and significance (3S) indicators. Further, the PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluations) technique has been used to measure the data quality dimensions considering 3S as criteria.FindingsThe effective indicators are identified from the past literature and the model confirmed with industry experts to measure these indicators. The results of this fuzzy AHP model show that the synthesis is recognized as the top positioned and most significant indicator followed by speed and significance are developed as the next level. These operational indicators contribute toward BDA and explore with their sub-categories' priority.Research limitations/implicationsThe outcomes of this study will facilitate the businesses that are contemplating this technology as a breakthrough, but it is both a challenge and opportunity for developers and experts. Big data has many risks and challenges related to economic, social, operational and political performance. The understanding of data quality dimensions provides insightful guidance to forecast accurate demand, solve a complex problem and make collaboration in supply chain management performance.Originality/valueBig data is one of the most popular technology concepts in the market today. People live in a world where every facet of life increasingly depends on big data and data science. This study creates awareness about the role of 3S encountered during big data quality by prioritizing using fuzzy AHP and PROMETHEE.

Adoption of ICTs as an emergent business strategy during and following COVID-19 crisis: evidence from Indian MSMEs

Abstract: PurposeThis study aims to identify how ICT appeared as an emergent business strategy and to investigate the impact of ICT adoption factors on the perceived benefits of micro, small and medium enterprises (MSMEs).Design/methodology/approachA total of 393 responses from Indian small and mid-size enterprises (SMEs) were collected for the final analysis. The study presents the partial least-squares structural equation modeling with the Chi-square test and descriptive analysis as a methodology based on numerous independent variables and one dependent variable.FindingsThe findings indicate that ICT adoption during and following the COVID-19 pandemic is constant in nature of the enterprise. Moreover, the results indicate that different adoption of ICT factors influence on perceived benefits of organizational performance of Indian MSMEs that lent good support except for the regulatory framework.Research limitations/implicationsThe implications of the current research help Indian MSMEs to take investment decisions in various technologies that help the organization. Furthermore, managers and practitioners help the organization in deciding which technology adoption factors are more critical to the betterment of the organization.Originality/valueThe study found certain ICT adoption factors that have a significant role in organizational performance in Indian MSMEs. Moreover, during COVID-19, investigate ICTs' role as a business strategy.

The position and role on patent citation network of the parking lot guidance system

Abstract: During the peak period of urban traffic, about one-third of vehicles are looking for parking spaces, resulting in air and noise pollution, and even traffic accidents due to emotional stress of driv...

Big Data; Potential, Challenges and Statistical Implications

Abstract: Big data are part of a paradigm shift that is significantly transforming statistical agencies, processes, and data analysis. While administrative and satellite data are already well established, the statistical community is now experimenting with structured and unstructured human-sourced, process-mediated, and machine-generated big data. The proposed SDN sets out a typology of big data for statistics and highlights that opportunities to exploit big data for official statistics will vary across countries and statistical domains. To illustrate the former, examples from a diverse set of countries are presented. To provide a balanced assessment on big data, the proposed SDN also discusses the key challenges that come with proprietary data from the private sector with regard to accessibility, representativeness, and sustainability. It concludes by discussing the implications for the statistical community going forward.

Best web service selection based on the decision making between QoS criteria of service

Abstract: Recently, extensive studies have been carried out on web service standards because of the necessity of developing large-scale applications in open environments. In particular, they enable services to be dynamically bound. However, current techniques fail to address the critical problem of selecting the right service instances. Service selection should be determined based on customer preferences and service level. We propose a best web service selection method which helps to find a service provider providing the optimal quality. Web service selection process was described with multi-criteria decision making approach(e.g. PROMETHEE) on the basis of evaluated values of qualities and the defined service level. The PROMETHEE method has advantages in comparison with the others(e.g. MAUT, AHP) as follows. First, the PROMETHEE method classifies alternatives which is difficult to be compared because of a trade-off relation of evaluation standards as non-comparable alternatives. Second, the PROMETHEE method is different from the AHP method in that there's no need to perform a pair-wise comparison again when comparative alternatives are added or deleted. Therefore, this method is a suitable approach in the web service selection problem. Because the problem has a lot of quality parameters which are measured and evaluated at the same time and frequently induces a drop of another quality parameter by the improvement of one quality attribute. Consequently, our approach enables applications to be dynamically configured at runtime in a manner that continually adapts to the preferences of the customers. We verify our approach through case study.

Addressing strategic human resource management practices for TQM: the case of an Indian tire manufacturing company

Abstract: PurposeThis study aims to identify SHRM (strategic human resource management) essential practices for the TQM (total quality management) program regarding an Indian tire manufacturing company and formulate an inclusive interrelationship to prioritize them.Design/methodology/approachSemistructured interview with ten experts from the company was made to give SHRM practices scores. The SLR (systematic literature review) and TOPSIS (technique for order of preference by similarity to ideal solution) techniques are used to establish the model for 12 key practices and rank them afterward.FindingsThe findings clearly show that strategic planning and staffing, teamwork and leadership development have appeared as the top three essential practices. Simultaneously, performance measurement and evaluation, work design and analysis and promotion are identified as the bottom three practices. These essential practices are identified as contributing attributes.Practical implicationsThe findings prioritize the SHRM practices as contributing attributes that help other tire manufacturing industries identify their key practices. Moreover, it provides the necessary inputs comprised of ten experts' decisions to become more active and well prepared.Originality/valueThe novelty of this study is to identify the key practices by using SLR and measured by the TOPSIS method to rank and consider a tire manufacturing company as a case-based approach to gain high productivity and competitive advantage.