Ajay Jha
@upes.ac.in
Department of Transportation Management, School of Business
University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Ashish Dwivedi, Dindayal Agrawal, Ajay Jha, and K. Mathiyazhagan
Elsevier BV
Pratima Verma, Vimal Kumar, Ankesh Mittal, Bhawana Rathore, Ajay Jha, and Muhammad Sabbir Rahman
Emerald
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.
Ajay Jha, Rohit Sindhwani, Ashish Dwivedi, and Venkataramanaiah Saddikuti
Emerald
Purpose The purpose of this study is to identify important criteria for sustainable recovery of digital entrepreneurship from distress situation using shared resources. During pandemic disruption, the importance of sharing economy in managing business efficiency is reflected through this research. Design/methodology/approach The present study advances the knowledge on shared resources in business by integrating case study approach with multi criteria decision-making (MCDM) model. A fuzzy analytic hierarchy process approach is adopted to compute criteria weights, and a fuzzy technique for order performance by similarity to ideal solution (TOPSIS) technique is used to rank the sharing economy entrepreneurial ventures during COVID-19 pandemic in the context of emerging economy. Findings The present study identified five most important enablers (technological innovation, technology expertise, convergence of virtual and physical spaces, collaboration rather than competition, and benefits to underserved groups through transparency) for sustainable recovery of sharing economy ventures in emerging economy. For example, the study highlights online tutoring through shared intellect as the most sought after sharing economy venture during pandemic disruption, which fulfills the identified enablers. Practical implications The proposed framework provides an accurate decision support tool to rank the various identified potential enablers of sharing economy during disruptions. Further, the approach is practically relevant to sharing economy entrepreneurs in selecting the best approach to recover sustainability during pandemic. Originality/value The study is unique in addressing the need of sustainability for digital ventures via sharing economy approach in emerging economy (India). To develop a conceptual framework, the present study incorporates a case based approach together with the hybrid MCDM model. Further, the extant literature on disruptions is enhanced by prioritizing the enablers for sharing economy during pandemic.
Vimal Kumar, Pratima Verma, Ajay Jha, Kuei-Kuei Lai, and Manh-Hoang Do
Emerald
PurposeThis research presents a study on the supply chain process of an Indian apparel industry considering various parameters involved. The study aims to identify the main parameters to improve the supply chain process and develop a comprehensive structural relationship to rank them to streamline the apparel supply chain process and business environment.Design/methodology/approachThe team of five experts from this apparel industry was made to give scores to multiple parameters. The TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) technique is used to develop the model for eleven key parameters and then rank them.FindingsBased on the data analysis the planning, customer and warehouse storage have emerged as top three key parameters while the non-replenishment approach, push and pull strategy and manufacturing of the product are identified as the bottom three parameters from a hierarchy level. These parameters have been ranked based on their contributing attributes in this apparel supply chain process.Research limitations/implicationsThe study provides an overall ranking of parameters and the implications are in the direction of helping the industry to improve its supply chain performances rather than focus only on productivity. Further, the key parameters are identified as critical inputs and show that the firms are being more proactive and well prepared comprised of the industry.Originality/valueThe study indicates that the key parameters are identified by this apparel brand to improve its supply chain process. The key supply chain process involves planning, manufacturing, distribution, end customer and returns logistics of the goods, etc. So, this research also provides the focused parameters on the supply chain performance received by end customer from the supplier and rank them for effectiveness and improve their overall organizational performance. It also provides a critical observation of their supply chain process improvement which includes different brand uses, strategies and approaches.
Ajay Jha, R.R.K. Sharma, Vimal Kumar, and Pratima Verma
Emerald
Purpose A well-designed supply chain performance measurement system, should account for not only the capabilities and performance attributes of the focal firm but also its supply chain partners. The purpose of this paper is to help design a system that strikes a balance between the strategic objectives of the focal firm and its supply partners vis-à-vis the requirements of supply chain performance (cost, quality, speed and customer taste). Design/methodology/approach A theoretical framework on the strategic supply chain performance measurement system is developed based on existing literature and subsequently tested using a survey on 136 successful manufacturing organizations in India. The organizations were clustered into three strategy types and compared using analysis of variance on ranks to look for differences in preference for performance parameters. Findings The study examined the five dimensions of the supply chain practices, namely, strategic supply/distribution network, customer relationship, internal operations, information sharing and social and environmental responsiveness. The empirical results demonstrate the inclusion of business strategy orientation in designing today’s supply chain and hence its performance measurement system. Not supported hypotheses were addressed in the light of contextual factors. Research limitations/implications The study is confined to finding preferences of non-financial aspects of supply chain performance and tier-1 suppliers. The research helps better design and benchmark supply chain performance metrics, based on the strategic choice of the firm. Originality/value This paper highlights the shortcomings in the existing performance measurement and gaps in the existing literature in the supply chain context. Further, it gives a holistic view of strategic supply chain performance measurement design.
Vimal Kumar, Ajay Jha, Pratima Verma, and Nagendra Kumar Sharma
CRC Press
Ajay Jha, R.R.K. Sharma, and Vimal Kumar
Emerald
PurposeThe study aims to add to the body of knowledge of open source tangible product management (also called open design). The objective is also to develop a guideline for efficient open source tangible product development and adoption.Design/methodology/approachThe exploratory research design using secondary data (like newspapers, magazines, research articles, bogs, papers, etc.) is used to analyze open source tangible product design challenges and enablers. The success stories of Open Source Software projects (OSS) were studied for identification of critical success factors and further their relevancy was tested in the two popular cases of open source drug discovery (malaria and tuberculosis)FindingsOpen innovation has become a part of competitive strategy of current businesses. It requires an efficient intellectual property protection regime for its implementation. However, in a market dominated by proprietary benefits, the open source technology development can serve as remedy for innovation needs of neglected sectors. The OSS literature revealed managing two classes of factors, namely technology sponsor level factors and environmental factors for efficiency and effectiveness. The case study analysis in the context of applicability of these OSS critical factors showed their limitations in open source tangible products, and highlighted understanding additional challenges and remedies.Research limitations/implicationsOpen source innovation is a collaborative effort involving inputs from various/diverse players, hence monitoring the effort and motivation level of the contributors is a cumbersome task. Only the information that is available online and in print media is taken as research inputs in this work. Also the data taken were from two case studies; a lot more case studies in the open design domain can progress the theory. The implications of this study are far-reaching in the areas where profit motivated proprietary efforts lack in addressing societal need. It provides guidelines for addressing those unmet needs by developing products in a collaborative way without intellectual property hurdles.Originality/valueThe essence of open design is becoming more vital, and there is a pressing need to build theory to support it, which still is elusive and dispersed. The study fills the gap using secondary data and case study approach.
Rupesh Kumar, Surendra Kansara, Deepak Bangwal, Akhil Damodaran, and Ajay Jha
Inderscience Publishers
Ashish Dwivedi, Dindayal Agrawal, Ajay Jha, Massimo Gastaldi, Sanjoy Kumar Paul, and Idiano D’Adamo
Springer Science and Business Media LLC
AbstractThe value chain refers to the source of competition to facilitate organizations to maximize and sustain value for their consumers. Value chain flexibility is necessary to build sustainable initiatives in addressing ambiguity. In the literature, there is a lack of framework to highlight the challenges to sustainable initiatives in value chain flexibility. This study fills this research gap by suggesting a framework for challenges to sustainable initiatives in value chain flexibility. In this study, thirteen potential challenges to sustainable initiatives in value chain flexibility are identified and an integrated model is developed. It adopts the modified Total Interpretive Structure Model and the Cross-Impact Matrix Multiplication Applied to Classification methodology. The mixed approach is used as the modified Total Interpretive Structure Model organizes the binary interactions among the challenges, while Cross-Impact Matrix Multiplication Applied to Classification analysis organizes specific precise assessments of the driving power and dependence of the challenges. The results of the study reflect that (i) lack of supplier commitment to sustainable products and (ii) lack of knowledge toward sustainability in value chains are the challenges that achieved the highest driving power. The challenge ‘inadequate communication among the suppliers in the value chain’ is at the highest level in the analysis. The proposed framework could help government and non-government bodies to formulate policies to efficiently address challenges to sustainable initiatives in value chain flexibility.
RRK Sharma, Md Amir, Ajay Jha, and Priyank Sinha
IEEE
Lot sizing problem aims to effectively utilize the production resources for meeting the demand targets. In this article, we compare the computational performance of the lot sizing formulation available in literature (see Verma and Sharma (2009): denoted as [S]) with the new formulation. New formulation [NF] has been developed by eliminating the backordering variables from the standard formulation (see Sharma and Sinha (2018)). Our numerical analysis on the random problems reveals that objective function value for the new formulation [NF] is better than the objective function value of standard formulation [S] with a statistical significance of 0.054, however CPU time of the formulation [S] is inferior to standard formulation with the statistical significance of 0.144. Thus it can be seen that new formulation [NF] has merit.
Rupesh Kumar, Ajay Jha, Akhil Damodaran, Deepak Bangwal, and Ashish Dwivedi
Emerald
PurposeThe purpose of this study is to investigate the challenges before India for electric vehicle (EV) adoption by 2030. The study further looks into the measures taken by the Government of India (GOI) to promote research and development in EV sector and what is yet to be done.Design/methodology/approachIn the present study, the challenges are identified allied to the commercialization of EVs in India. The data are collected, analyzed and compiled through secondary sources. The secondary data give a concise insight and comprehensive information regarding what is occurring around the globe as well as in the Indian context. Further, the challenges are investigated through a focus group study consisting of 11 participants from industry and academia.FindingsThe findings from the study are the critical roles of sharing economy and public utilities in the promotion of EV adoption, given the high cost of EV, lack of infrastructure and poor purchasing power of Indian customers. The sharing economy perspective provides various opportunities for the government to manage the resources (electric-powered transport system) optimally. Further, the study compares the global perspective in assigning the target figures.Research limitations/implicationsThe study highlights the facilitating role of the shared format in EV technology promotion but ignores the hurdles that can come in its implementations. Also, the focus group study has its limitation as it relies more on participants' perceptions and opinions.Originality/valueThe present study assists GOI and various stakeholders in having a realistic plan rather than daydreaming with overambitious goals. The diffusion of technology as a shared format (especially in the context of EV) has not been academically approached in the past literature.
Pratima Verma, Vimal Kumar, Ajay Jha, Vignaesh Muthukumaar, Manh‐Hoang Do, Nagendra K. Sharma, and Sachin Gupta
Wiley
R. R. K. Sharma, Ajay Jha, and Sandeep S Rajput
IEEE
Companies in high technology area either have to lead and set the industry standard, or quickly follow the prevalent, or risk becoming obsolete. Learnings from this paper are following: First, the Innovators tend to develop proprietary technology to take advantage of first to market and the late entrants try to make up by developing open source technology. However the proprietary strategy is not always successful in launching improved substitute owing to the network effect and switching cost and the market may favor an inferior product. Second, the elite products are generally produced under proprietary technology, whereas broad base products are aimed by open Source. Third, with time the proprietary systems are found expensive to maintain, and are made open to sustain. Fourth, proprietary technology aims for vertically integrated supply chain leading to full ownership of upstream and downstream supply components. Finally the long term strategy calls for open source for greater market size.