Department of Management

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Understanding the Effect of Social Media Use on Psychological Stress During the COVID-19 Pandemic
(IGI Global, 2022) Saxena, Deepak
This study examines the effect of the modern technology of social media on psychological stress during Irish COVID-19 quarantine restrictions. Literature indicates mixed findings regarding social media usage and psychological stress. Acknowledging its multifaceted nature, social media use in this study is examined through the category usage motivators of consuming, participating, and producing. Usage motivators significantly indicate variations in terms of impact on stress. Social media use for the purpose of consuming is moderately correlated with increased levels of psychological stress. Social media use for the purpose of participating exhibits a weak correlation with decreasing levels of psychological stress. Social media use for the purpose of producing exhibits no significant relationship with psychological stress during quarantine. Findings of this study are valuable for government and corporate policy makers and mental health and marketing professionals, with implications in psychological wellbeing practices and mindful social media use during quarantine.
Towards Energy Efficient Cloud Computing: Research Directions and Methodological Approach
(Springer, 2021-03-26) Saxena, Deepak
Cloud computing has revolutionized the IT industry by allowing the supply of elastic computing tools on demand as pay-as-you-go services such as SaaS, PaaS, and IaaS (Beloglazov, Energy-efficient management of virtual machines in data centers for cloud computing. PhD thesis, 2013; Farahnakian et al., Energy and performance: management of virtual machines: provisioning, placement, and consolidation. 2016). Cloud computing has contributed to the reinventing of the way technology resources such as servers, storage, private networks, application platforms, and software services are procured and provisioned. A cloud consumer only requires an Internet connection to connect to a cloud service provider to use these services without placing undue pressure on the resources of their computer or mobile device. A medium-sized enterprise may outsource the demand for computing resources to the Cloud and escape high front-end costs that could be spent on private computational resources and thereby save costs that may arise from hardware and software maintenance and upgrades. A giant enterprise, meanwhile, can also create its own private cloud data center to satisfy the demand for computing services and enhance the process of resource management and provisioning. However, cloud computing infrastructure requires massive energy, sometimes even exceeding the energy requirements of a mid-size town. This chapter discusses the need for energy efficiency and the methodological approach needed to achieve energy efficiency.
Responsible Machine Learning for Ethical Artificial Intelligence in Business and Industry
(IGI Global, 2021) Saxena, Deepak
Artificial intelligence (AI) systems have become a new reality of modern life. They have become ubiquitous to virtually all socio-economic activities in business and industry. With the extent of AI's influence on our lives, it is an imperative to focus our attention on the ethics of AI. While humans develop their moral and ethical framework via self-awareness and reflection, the current generation of AI lacks these abilities. Drawing from the concept of human-AI hybrid, this chapter offers managerial and developers' action towards responsible machine learning for ethical artificial intelligence. The actions consist of privacy by design, development of explainable AI, identification and removal of inherent biases, and most importantly, using AI as a moral enabler. Application of these action would not only help towards ethical AI; it would also help in supporting moral development of human-AI hybrid.
Inventory Modelling for technology generation products under uncertain trade credit terms and imprecise procurement costs
(OSCM, 2022) Chanda, Udayan; Nagpal, Gaurav
The inventory policies for any product under the trade credit mechanism are influenced by the procurement price per unit and the credit period offered by the seller to the buyer. This paper develops an inventory model for the technology generations under the imprecise trade credit period and the imprecise procurement cost. It considers the demand that is credit-linked and governed by innovation diffusion as well. The imprecise nature of the parameters is captured by the use of fuzzy numbers. The trapezoidal membership function has been used to fuzzify the profit function with the imprecise parameters, and then the centroid method is used to de-fuzzify the profit. The numerical illustrations have been performed, followed by the sensitivity analysis with the launch timing of the second generation product. A few important implications for the inventory practitioners and the possible extensions of this work have also been discussed.
Measuring service quality in Indian automobile aftersales: AutoIND scale
(Inder Science, 2023) Chanda, Udayan; Sharma, Satyendra Kumar
The purpose of this paper is to examine the existing service quality measurement scales in the literature on automobile after-sales service. It seeks to develop and validate a service quality measurement scale for Indian passenger car industry's after-sales segment, thereby enhancing service quality (SQ) and customer satisfaction. The study's research design consists of a combination of literature review, exploratory interview and a questionnaire survey conducted through interviews. This paper develops a pilot SQ measurement scale to assess SQ in the Indian passenger car industry's after-sales segment. Apart from the five SERVQUAL dimensions in the extant literature, two new dimensions of service failure and service recovery have been identified and included in the scale developed to address the specific features of the Indian automobile industry. The scale developed in this research will provide a framework towards the development of a measurement scale for after sales services in auto industry.
P-Model of Inventory Optimization for high technology multi-generation products under limited warehouse storage space
(Inder Science, 2020-07) Chanda, Udayan; Nagpal, Gaurav
This research work puts forward the inventory optimization model for the high technology multi-generation products under the situation of limited warehouse storage space. It is assumed that the manufacturer has an own space which has a lesser opportunity cost of usage as compared to another rented space, that carries higher charges on per unit area basis. Therefore, the manufacturer utilizes the own storage space for the period of time where his own space is sufficient to keep the inventories. When its inhouse space is not sufficient to store all the inventories, it stores the excess inventories at the rented space. While the research work has been done on various demand patterns under such a scenario, there is no research present on the inventory optimization under storage space constraints for the generations of innovative products whose demand follow the Norton Bass Model of Innovation Diffusion. This paper lays down a model for inventory optimization, but also puts forward a few theorems on the dynamics of how the model behaves with the change in innovation effect, imitation effect, with the rent of the leased location and with the storage capacity of own location. Finally, the paper performs numerical illustrations to show the behavior of the proposed model.
Multi-Period EOQ Model for Multi-Generation Technology Products With Short Product Life Cycles
(ACM Digital Library, 2022-07) Chanda, Udayan; Nagpal, Gaurav; Jasti, Naga Vamsi Krishna
In this paper, the multi-period EOQ model is developed for the technology products that have multiple generations co-existing in the market, with each of them having a very short product life cycle. The paper first develops the framework for computation of inventory-related costs and then minimizes the total replenishment costs using random search technique and approximating the non-linear expressions while using Simpson’s Rule for integration. The paper also provides numerical illustrations and establishes a few important theorems that relate the EOQ to the innovation of diffusions. It is found that the total replenishment cost curve, drawn on the EOQ axis in the case of technology generations is convex to the origin. Since the objective function is highly non-linear, the genetic algorithm has been used to find the solution to the problem. The study also suggests that the faster diffusion of the next generations has a conflicting effect on the EOQ of the first generation in the case of pooled and non-pooled logistics.
Inventory Replenishment Policies for Two Successive Generations of Technology Products Under Permissible Delay in Payments
(IGI Global, 2022) Chanda, Udayan; Nagpal, Gaurav
In this age of digitalization, when every industry is undergoing technological disruption, there is a big role of digital gadgets and technology products. A key feature of these digital gadgets is the short length of the product life cycle, since the newer and more advanced generations of technologies are developed regularly to replace the earlier conventional technologies. The traditional EOQ models that assume a constant demand cannot be used here. This research paper formulates an inventory optimization model for the multi-generational products under the trade credits and the credit-linked and innovation diffusion dependent demand. The study also performs a numerical illustration of the proposed model, and establishes important dynamics among the key variables. It also performs the sensitivity analysis with the cost of credit and the trade credit period. The paper concludes with the managerial implications for the inventory practitioners and the possible areas of extension for this research in the future.
Supply-side risk modelling using Bayesian network approach
(Taylor & Francis, 2022-02) Chanda, Udayan; Sharma, Satyendra Kumar; Routroy, Srikanta
Organisations’ vulnerability to risks exponentially increased in the past decade, thereby highlighting the need to develop additional effective risk management strategies. This research uses a systematic literature review as a foundation for designing a supply risk model that uses a Bayesian belief network. The proposed model aims to identify the most critical objective and subjective risk factors influencing supply chain networks. Moreover, the proposed methodology has been demonstrated through a case study conducted in an Indian manufacturing, in which inputs were taken from supply chain and risk management experts. Hugin Expert software was used to design and run simultaneous simulations on the Bayesian network. The top three factors found to influence business profitability were delays, product technology, and fuel price. The proposed model can be reengineered as conditions change and new information becomes available, thereby ensuring that risk analysis remains current and relevant along the timeline of the any disruption.
Inventory replenishment policies for two successive generations price-sensitive technology products
(American Institute of Mathematical Sciences, 2022-05) Chanda, Udayan; Nagpal, Gaurav
The high technology products come in generations, where the demand for newer technology generations is strongly influenced by the installed base of earlier generations (such as computers, cameras, notebooks, etc). However, the effect of technology substitution on inventory replenishment policies has received little attention in the supply chain literature. In the hi-technology market, consumers' purchasing capability, the utility of a product along with the entry of the advanced generation product influence the market expansion/contraction of the products. In this study, the impact of parallel diffusion of two successive generations' products on inventory policies of the monopolist has been analysed. The demand models have been characterised by considering the life-cycle dynamics for a P-type inventory system. The purpose of this paper is to develop a model for joint pricing and replenishment of technology generation products. The model has been solved by using a genetic algorithm technique. The impact of yearly price drop and the price sensitivity of demand on the profit margins vis-à-vis on replenishment policies has also been studied. The paper also brings forward the dynamics of the launch of newer generations and the pricing strategies on optimal inventory replenishment policies. Numerical illustrations have also been covered in the paper.
The First Half-Century of Decision Modelling for Substitutable Products: A Literature Review and Bibliographic Analysis
(OSCM, 2021) Chanda, Udayan; Nagpal, Gaurav
Due to the resource constraints of the factors of production (land, capital, capacity, etc.), the firms have to rationalize the assortment of products that they deal in. In such a situation, a consumer whose requirement for a preferred product may not get served from the existing inventories with the seller, may go for some other alternative product. A lot of research work in the past has been done on this demand substitution and its implications upon the assortment optimization, inventory optimization and price optimization. The first work on modelling for substitutable demand is attributed to 1970. Considering the same, the authors decided to do a review of the half-century of work on the modelling for substitutable products. The paper gives a detailed analysis of the published research articles around demand substitution and also discusses the achievements of the existing research. The article also gives a few possibilities of the future extensions to this body of knowledge on the management of substitutable products.
Optimal inventory policies for short life cycle successive generations’ technology products
(Taylor & Francis, 2021-03) Chanda, Udayan; Nagpal, Gaurav
In this paper, a new Economic Order Quantity (EOQ) model for a successive generation of technology products has been discussed. The classical EOQ model is based on the assumption that the demand rate is constant. Hence it cannot be used for technology products where competition-substitution among products is a usual phenomenon. To address this problem, the EOQ model proposed in this article is considered a demand model for a technology product that follows the innovation-diffusion process. A numerical example has been illustrated and a comprehensive sensitivity analysis is conducted to understand the path of the optimal planning horizon and optimal costs under varied innovation and imitation effect. The sensitivity analysis of the introduction timing of the second generation has been performed to know the applicability of the model in actual circumstances. The behavior of the model has been discussed in detail in the numerical illustration section.
Economic order quantity model for two generation consecutive technology products under permissible delay in payments
(IDEAS is a RePEc, 2021) Chanda, Udayan; Nagpal, Gaurav
In this article, we discussed optimal replenishment policies for two succeeding generations' technology products under partial trade credit financing. It is often seen that in technology market, advanced generation product plays an important role in cannibalising the market of existing generation product. Thus, precise estimation of demand of technology generations' product is critical for taking any policy decisions. Demand estimation of technology products is a complex process, as the consumer buying behaviour of technology generational products is not only depends on marketing mix variables but also associated with the time-to-market phenomenon of new technologies. In technology market, interaction among users of different generational products controls the rate of substitution of older technology products with the new one. Therefore, due to the substitution nature of demand of multi-generation product, it is important to incorporate the interaction-substitution effect in replenishment policies for this kind of products. We used life cycle dynamics to project demand rates of technology generations. In this paper, we formulate the total cost function for five different situations depending upon the new generation introduction timing and length of the trade credit period. A detail sensitivity analysis is been performed to explore the efficacy of the model in a given situation.
Adoption and Diffusion of Hi-Technology Product and Related Inventory Policies: An Integrative Literature Review
(IGI Global, 2020) Chanda, Udayan; Nagpal, Gaurav
The objective of this review article is to study the published research on the inventory modeling and optimization for substitutable technology products with a short product life cycle. This review explains the demand dynamics of technology generation products and how to administer supply chain management of this kind of products than any other functional products. The article does a review of the demand models proposed on the diffusion of innovation products, and then, moves on to the literature review of the multi-item inventory models, followed by the literature review of the inventory modeling of substitutable items. In order to ensure the quality, this study covers the review of the research papers mostly published in reputed SCI or ABDC rated journals. The study discovers that the research that has been done on the inventory optimization of multi generation technology products is not only rare but also very restrictive in its scope and assumptions. The study then proposes the directions for the future research.
Does Firm Size Influence Leverage? Evidence from India
(Sage, 2020-02) Bhat, Anil Kumar; Chanda, Udayan
This study aims to investigate the size–leverage relationship in the context of India—one of the important emerging economies. Most of the studies that have tested the relationship between firm size and leverage have been conducted in the developed economies. For testing the much-discussed size–leverage relationship, we employ a large sample of firms for the study over a time span of 17 years from 2002 to 2018. Our findings support the negative size–leverage relationship, confirming the propositions of the pecking order theory. The study has implications for policymakers regarding the development of corporate debt market in India.
Optimal Investment of Resources in Creation of Human Capital: A Control Theoretic Approach
(International Journal of Operations and Quantitative Management, 2019-12) Chanda, Udayan; Goyal, Praveen
Many recent studies on organizational development have suggested that human capital attributes have a strong and direct effect on organizational performance. Thus, a cost-effective optimal human capital development plan can be of utmost importance for a firm to sustain in this competitive environment. Herein, we studied the optimal investment path on human capital under a given budgetary constraint to improve the organizational performance. Cobb-Douglas production functions (of human capital) are used to derive the optimal time path of a firm’s investment by employing optimal control theory. The economic explanations and suggestions of the model solutions are also discussed in detail. We expect the experimental results obtained through the analysis will assist us to recognize the importance of each chosen parameter and their credence.
A Bayesian network model on the interlinkage between Socially Responsible HRM, employee satisfaction, employee commitment and organizational performance
(Taylor & Francis, 2019-08) Chanda, Udayan; Goyal, Pravin
In recent years several studies have been made to understand the impact of Socially Responsible HRM practices on Organizational Performance. Employee progress, community and environment play an important role in the sustainable growth of an organization. Thus, organizations are always looking for the ways to improve the employee satisfaction vis-a-vis commitment to improve the performance. Recent studies have shown that as employees are important stakeholder, hence formulating proper Socially Responsible HRM practices may help organization to better the returns on assets. The main objective of the study is to identify the relationship among various dimensions of Socially Responsible HRM practices with dimensions of employee satisfaction, employee commitment and organizational performance for Indian manufacturing sector by using Bayesian Network approach. Results of the study establish the relationship between dimensions of Socially Responsible HRM and Organizational Performance.
Optimal ordering policy for short life-cycle products under credit financing with dynamic adoption in supply chain
(Taylor & Francis, 2019-05) Chanda, Udayan
Traditional inventory models are mostly ignorant of the life cycle dynamics of a technology product; hence, they often fail to identify different dimensions of inventory research. This paper attempts to investigate the relationship between adoption behavior of customers using life cycle dynamics and associated trade credit policies in order to optimize the total inventory cost. The demand model used in this paper treats sales as a function of awareness diffusion and adoption. Awareness is considered as a function of feedback effects from users/customers. Retailer’s optimal strategies for short life cycle product under credit financing were determined analytically. Finally, numerical examples have been used to support the theoretical results. Theoretical results have further been used to gain some managerial insights.
Assessing Impact of Human Capital, SRHRM and Employee Related Factors on Firm Performance
(World Scientific, 2019) Goyal, Praveen; Chanda, Udayan
In today’s competitive environment, the Indian manufacturing sector is feeling the need to develop new strategies to increase employee performance by improving the job satisfaction and reducing stress. Improving employee performance is one of the important drivers of the organization’s growth. In recent years, organizations are also investing a great deal on human capital to capitalize on employee productivity. The objective of this study is to identify and assess the association among different individual level factors and their impact on the organization performance in the Indian Manufacturing companies. Partial least square (PLS) approach was used to examine the relationships among various factors that lead to employee commitment and organizational performance. Results of this study can provide an important reference for both academicians and practitioners for effectively improving employee satisfaction, employee commitment to increase the economic performance of the organization.
Optimization of EOQ Model for New Products under Multi-Stage Adoption Process
(World Scientific, 2019) Chanda, Udayan
The available literature on new product sales growth models mostly ignores two important aspects of technology diffusion: diffusion of awareness and the actual adoption. This characteristic of technology adoption is extremely important from inventory management perspective as buying decision is often influenced due to time lag between information propagation and actual adoptions. As high-technology market is extremely unpredictable, interactions between technological evolutions and customer feedback effects play an important role in technology diffusion. The demand models mostly considered in inventory literature to develop economic order quantity (EOQ) model ignore this important element of technology diffusion. In this paper, we proposed an EOQ model for high-technology products by incorporating customer feedback effects along with market heterogeneity to optimize the total inventory cost. The demand model considered in the paper follows lifecycle phenomenon and is sensitive to unit selling price. To remove any ambiguity pertaining to costs, fuzzy nature of ordering and inventory carrying cost is considered in the paper.