Browsing by Author "Chanda, Udayan"

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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.
Adoption and usage of the electronic national agriculture market: a literature review
(CRC Press, 2023) Dutta, Nirankush; Chanda, Udayan
Agricultural marketing is one of the lifelines for a sizeable population of India and it contributes 25 percent of the GDP. An effective agricultural marketing system can help farmers market their products at a fair and reasonable price. In recent years due to technological breakthroughs, the Indian agriculture sector is experiencing substantial shifts in irrigation strategies and the result is reflected in the surplus production of crops. Despite record production in crops the visible changes in farmers’ earnings are very negligible. The more profitable production of crops emphasizes the importance of agricultural marketing for the inclusive development of the agriculture and welfare of the farmers. “Thus the government and other organizations are trying to address the key challenges of agriculture in India, including small holdings of farmers, primary and secondary processing, supply chain, the infrastructure supporting the efficient use of resources and marketing, and reducing intermediaries in the market” (Sharma 2021). The National Agriculture Market (eNAM)- a pan-India electronic trading portal introduced in April 2016 to connect the Agricultural Produce Market Committees (APMC) mandis and to set up an integrated nationwide market for agricultural commodities. “It unites surplus production regions with deficit regions through an online platform, which may lead to better market competition, and thus better prices for farmers for their produce” (Venkatesh et al, 2021). This initiative was widely considered to be a game changer for farmers and the overall agricultural marketing sector of India. The present research paper reviews existing literature on the adoption of the e-NAM platform across different Indian states to highlight the status of adoption and acceptance by its various stakeholders
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.
A Bayesian Network Model on the association between CSR, perceived service quality and customer loyalty in Indian Banking Industry
(Elsevier, 2017-04) Chanda, Udayan; Goyal, Praveen
Corporate Social Responsibility has become a buzzword in the contemporary era. Decision makers are including CSR as important part of company’s corporate strategy. Indian banking industry is also facing huge challenges and looking for the avenues to create competitive advantage to retain and attract the customer. This study aims at identifying the association of various CSR initiatives on the perceived service quality and customer loyalty in the Indian perspective by using Bayesian Network analysis. Results of the study show the different dimensions of CSR that establishes relationship with the perceived service quality and customer loyalty.
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.
Bayesian network on labour dissonance: a social sector development challenge to India
(Taylor & Francis, 2016-01) Chanda, Udayan
India's unorganized labour force contributes about one third of the total labour sector. The scenario is even worse in the Indian automotive industry which employs a little over 7% on a permanent basis. Problems get exaggerated due to the outdated labour laws, ironically established to support and protect workers. The disappointing areas in the labour contract act and labour laws have led to unfair wage practices and a hostile work environment, giving way to labour discord. This research paper discusses the key issues of labour dissonance in the Indian automobile industry using a Bayesian network analysis. Real-life case-study examples from the Indian automobile industry were considered to identify the rationale behind labour unrest. Bayesian analysis of a set of 250 responses helped us to understand the associations among key attributes of labour dissatisfaction.
Click-Through Rate: An Overview of Scientific Research in Management
(CRC Press, 2023) Sharma, Yashvardhan; Chanda, Udayan
Since the introduction of online advertising, an increasing number of advertisers and firms are relying on this ad type to acquire consumers, making it an important revenue source for search engines and other internet giants like Google, Amazon, etc. Clicks are used as a metric in two ways: (i) for advertisers, it is used to measure the effectiveness of an advertisement, and (ii) for internet companies, it is used as a quality metric for their search engine or website. The click-through rate is the ratio of the number of impressions to the number of clicks of an advertisement. Managers are using this metric to allocate the budget for their advertisement campaigns based on their effectiveness. In the last decade, due to the growing industry demand, it has attracted scholars from industry and academia. This literature review article examines click-through rate evolution from an empirical standpoint using the bibliometric methods, reviewing 596 articles from the Scopus index. This review article (i) identifies the most influential articles, authors, and journals, serving as a baseline for future research, and (ii) charts the evolution of the topic over the last decade, assisting managers and future researchers in gaining a performance-based comprehensive view of click-through rate.
CTR Prediction: A Bibliometric Review of Scientific Literature
(CRC Press, 2023) Sharma, Yashvardhan; Chanda, Udayan
Internet giants like Google, Facebook, and Amazon have relied heavily on revenue from online advertising sales in recent years. The Click-through rate of an advertisement is the percentage of people who clicked it out of those who viewed it. The CTR as a metric represents the performance of their online advertisements. For over two decades now, researchers in academia and industry have paid great attention to getting good CTR prediction accuracy because of the demand it has generated in the digital world. This paper reviews the scholarly literature on CTR prediction during the previous decade by a bibliometric analysis of 1051 publications from journals indexed by Scopus. The goals of this research are to (1) conduct a structured quantitative analysis of the bibliometric data, (2) chart the development of CTR Prediction research, and (3) identify the most recent and relevant research literature and viewpoints in the field. A handful of studies have been conducted on this subject, and they have presented an in-depth analysis of specific methods and learning models being applied for CTR prediction. In addition to the previously submitted studies, this literature review aims to provide an overall bibliometric analysis showing the evolution of techniques employed for CTR prediction in the articles published over the last ten years, using a combination of bibliographic coupling, citation, and co-citation. The outcome of this literature evaluation will aid future researchers in gaining a deeper comprehension of the scientific studies around CTR prediction.
Determining adoption pattern with pricing using two-dimensional innovation diffusion model
(Elsevier, 2010) Chanda, Udayan
Studying the dynamics of the technology diffusions under the key determinants that influence the adoption of a technology across time and/or space into the market is crucial to assess the business case for new technologies. The topic diffusion has been widely studied by researchers from different disciplines, including Sociology, Economics, Psychology and Marketing. However a substantial amount of research has been focused on one dimension: either to examine the individual's adoption of an innovation or to explain the time path of adoption of technologies typically follows an S-shaped curve. The other dimensions of the diffusion of an innovation, has gained less attention. In this paper, we derive a two-dimensional technology diffusion innovation model which combines the adoption time of technological diffusion and price of the technology product. In the proposed model technological adoptions and the role of other dimensions are explicitly taken into consideration by using the classical Cobb–Douglas production function. The model is based on two main assumptions: the rate of adoption growth decreases in price and that there is diminishing returns to time because initial market size is fixed. The proposed model is also validated on a number of datasets and compared with established models. The empirical analysis shows that the model performs better than other one-dimensional diffusion model in terms of parameter estimation and model validity.
Developing a Bayesian belief network model for prediction of R&D project success
(Taylor & Francis, 2017-03) Sharma, Satyendra Kumar; Chanda, Udayan
The project success is critical to the business performance in the era of fierce competition and globalization. The basis for project success lies in the capabilities of managing risks effectively. Innovation has always been considerably risky; however, managing Research and Development (R&D) project risks has become even more important given today’s tight schedules and limited resources. Risk management has to be an integral part of the development process. The purpose of this research is to develop a model to assess and estimate the risk exposure of an R&D project. A risk quantification model based on the Bayesian belief network is proposed, which is effective in capturing the interaction between various risk factors. The aim of this model is to empower the project managers to predict the failure risk probability of R&D projects.
Development of software reliability growth model incorporating enhancement of features and related release policy
(Springer, 2010-07) Chanda, Udayan
The software industry can be considered as the typical high technology industry where rate of innovation and knowledge creation plays a pivotal role for continued firm growth. In the last few decades it has been observed that the world of software development management has evolved rapidly due to the intensified market competition. In particular the use of feature-addition model of software products in the industry is fast becoming the commonplace. The up-gradation model can be characterized by increasing the number of features in the software that will give the firm competitive edge in the market. The up-gradation of the system is done by extending it through add-ons, interfacing with other applications, etc. Continuous up-gradation of software’s also brings complexity in the systems once it failed to work properly. In recent years, there has been a growing interest to predict the link between the rates of failure and the reliability of software. Many software reliability growth models (SRGM) have been proposed over past three decades that estimate the reliability of a software system as it undergoes changes through the removal of failure causing faults. But unfortunately most of the models did not consider anything about the increase in failure rate once an up-gradation is made on the software. The objective of this paper is to propose the software reliability growth model that incorporates the effect of enhancement of features on software during testing and debugging process. In addition, we have also discussed the related optimal release time policy that minimizes the total cost.
A Differential Evolution Approach for Software Testing Effort Allocation
(Journal of Industrial and Intelligent Information, 2013-06) Chanda, Udayan
Software reliability playing a major role in the industry. Because it carefully plan and guide to the developer and tester so that software developing team develop more reliable software faster and cheaper. Distribution of limited testing efforts to a software development project is a difficult task for team leaders. The challenges become complex when the nature of the development process is considered in the dynamic environment. For dynamic allocation of effort we proposed using differential evolution. Several software reliability growth models (SRGMs) have been proposed in last decade to minimize the total testing effort expenditures, but mostly under static assumption. The main intention of this article is to distribute total testing resource optimally under dynamic condition. An elaborate optimization policy based on the optimal control theory is proposed using differential evolution. Differential Evolution is an improved version of Genetic Algorithm for faster optimization.
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.
Dynamic Effort Allocation Problem Using Genetic Algorithm Approach
(MECS Press, 2014-06) Chanda, Udayan
Effort distribution plays a major role in software engineering field. Because the limited price projects are becoming common today, the process of effort estimation becomes crucial, to control the budget agreed upon. In last 10 years, numerous software reliability growth models (SRGM) have been developed but majority of model are under static assumption. The basic goal of this article is to explore an optimal resource allocation plan to minimize the software cost throughout the testing phase and operational phase under dynamic condition using genetic algorithm technique. This article also studies the resource allocation problems optimally for various conditions by investigating the activities of the model parameters and also suggests policies for the optimal release time of the software in market place.
Dynamic Optimal Advertising Expenditure Strategies for Two Successive Generations of High Technology Products
(World Scientific, 2009) Chanda, Udayan
Advertising plays a very important role in drawing consumer attention to new-products and in encouraging early adoptions. The problem of drawing optimal advertising plans for innovations have therefore has received a lot of attention from marketing managers and researchers. But there is need for further research on problems pertaining to new-products that are part of technological generations. This chapter deals with the determination of optimal advertising expenditure for two-generation consumer durables. The model considers intergenerational diffusion effect and also introduces a framework for modeling innovation diffusion for two competing generations.
Dynamic Optimal Control Policy in Price and Quality for High Technology Product
(World Scientific, 2008-04) Chanda, Udayan
This paper studies optimal control policies of quality level and price for the introduction of a new product with two competing technology generations in a dynamic environment and also proposes a new model in this regard. Lots of work has been done to study the optimal policies pertaining to explanatory variables like price, promotional effort, quality, time etc. In comparison high technology products have received less attention. The proposed model is a combination of diffusion models and the cost function, which is capable of estimating the future profit trends. The new model uses the relationship between the repeat purchasers and the new purchasers in the overall diffusion of a new technology over multiple generations, by separately identifying the two types of adopters.
Economic order quantity model for new product under fuzzy environment where demand follows innovation diffusion process with salvage value
(Inder Science, 2016-05) Chanda, Udayan
Diffusion pattern of new products have been well-documented in literature but research on integration of growth model and inventory policies are still scarce. Globalisation and technological breakthroughs' are creating significant risks of obsolescence at the product level. This calls for integration of diffusion dynamics in formulation of economic ordering policies for technology products. Unfortunately, most of the diffusion models available in literature do not recognise uncertainty in diffusion parameters, making it difficult to use in inventory-models. Here, we propose an economic order quantity model using fuzzy logic for new product where demand rate follows innovation diffusion process. Effect of deterioration is incorporated by considering the salvage value in the cost component. The comprehensive sensitivity analysis with respect to different parameters has also been performed to illustrate the effectiveness and behaviour of the model.
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.
Economic order quantity model on inflationary conditions with demand influenced by innovation diffusion criterion
(Inder Science, 2012) Chanda, Udayan
In this paper, an inventory model has been proposed based on the explicit assumptions of interaction of marketing parameters to the optimal inventory replenishment policy. This study applies the discounted cash flow (DCF) approach for the analysis of the replenishment problem over a finite planning horizon. The demand rate is a function of time and is assumed to be driven by innovation diffusion process. In addition, a numerical example is performed justifying the need of incorporating the effect of innovation along with the effect of inflation on the optimal inventory replenishment. Sensitivity analysis is also performed to discuss the effectiveness of the proposed framework.
Economic order quantity model under fuzzy sense with demand follows Bass’s innovation diffusion process
(Inder Science, 2013-08) Chanda, Udayan
The economic order quantity (EOQ) model is usually not paid attention to make the model more realistic. The realistic EOQ model can bring a significant change while evaluating the profit and loss of any organisation. In this paper a mathematical model has been developed for obtaining the EOQ in which the demand of the product is assumed to follow an innovative imitative behaviour as proposed by Bass (1969). The theory of innovation-diffusion has been incorporated in this model. To make the model more realistic an attempt has been made to solve the model in light of fuzzy set theory under the trapezoidal membership function. The coefficient of innovation, the coefficient of imitation and the inventory carrying cost is assumed to be fuzzy numbers with trapezoidal membership function. By the median rule of defuzzification, total cost formula has been derived in the fuzzy sense in order to obtain the optimal order quantity. The effectiveness of this model is illustrated with a numerical example and sensitivity analysis of the optimal solution with respect to different parameters of the system is performed.