The dynamicity of the technology market and varied consumer tastes make the technology product market highly unpredictable and complex. Besides, due to competition and fast breakthroughs in the technology market, it can be observed that in recent years, the product life cycle has shortened significantly. It created immense pressure on managers to develop inventory policies corresponding to actual market realities. Economics order quantity (EOQ) models are often used to develop inventory policies. However, due to the variable nature of the demand rate function of technology products, the traditional EOQ models may not be useful for developing replenishment policies for technology products. In addition to the consumer adoption process, inventory managers also face the challenge of imperfect quality products while strategizing business policies. Imperfect quality products can come from flawed transport and storage conditions, or they may come due to the faulty production process. Proper inspection or screening of the lot is important for removing the desired level of defective items before delivery to the customers. In this paper, we propose a new EOQ model for technology items with imperfect quality where the demand rate will follow life-cycle dynamics, and sales are treated as a function of product awareness, utility, and consumer affordability. To confirm the validity of the proposed framework, a numerical analysis is performed under different market conditions.

The Mangala Field is located in the Barmer Basin in north-west of India (Fig. 1). The field has oil in-place volumes of 1.3 billion barrels, with an estimated recovery factor of 43% with polymer flood. Production began in 2009 and water injection in 2010. Polymer flooding started in 2015 in all layers at field scale. A successful ASP pilot was conducted in 201012 and it envisaged to roll it out gradually to full field in due course of time. The main reservoir units in the Mangala Field are the fluvial sandstones of the Fatehgarh Formation. The targeted reservoir horizon (FM1), is quite heterogeneous. The permeability range varies from 200 mD to several Darcies (4-5 Darcies) and sandbody connectivity is complex in the reservoir that is interpreted as a fluvial to lacustrine environment. This heterogeneity affects polymer sweep efficiency and calls for an in-Depth Conformance solution. Two candidate patterns were selected for further evaluation of conformance technologies. The selection criteria were based on early breakthrough, non-uniform injection profiles, cross-section analysis to check connectivities and low recovery factor with higher remaining oil. Several chemical conformance options were considered. Injection of gels are constrained by the gelation time, which does not typically exceed a few days. Injection of Microgels is preferred since the single component product acts by simple adsorption and can thus propagate deep in the reservoir. Moreover, the Microgel size which is above 2 μm, prevents the invasion of low-permeability intervals by a size-exclusion process. The product has thus a natural tendency to invade high permeability sandbodies (already swept). Different Microgel species have been submitted to lab tests. SMG Microgels keep their original size, while EMG Microgels expand with time and temperature. A major challenge to overcome is the existence of a polymer layer adsorbed on pore walls, which creates a barrier to Microgel adsorption. Finally, an EMG species whose chemistry induces high adsorption level has been qualified. The adsorption level is as high as 200 μg/g and the product induces a permeability reduction to water of around 8.5. Reservoir simulations were conducted afterwards to optimize the injection design (volume and duration) and draw performance forecasts. The reservoir simulation software used for the study can perform a dual polymer simulation, so two different species of polymers can be simulated. The sector model was made of two inverted contiguous 5-spot patterns with central injectors. The best scenario consisted in injecting the EMG at a concentration of 0.3% for 15-30 days. The deployment is simple since the product (delivered as liquid emulsion) can be injected with a volumetric pump of the water injection line directly. Additional oil production is expected to be as high as 95,500 bbls in 4.5 years. Microgel technology, has been successfully applied in waterflood projects in heterogeneous sandstone reservoirs and is shown to be applicable in ongoing polymer flood as remedial injection to solve conformance problems as well as produce significant incremental oil currently by-passed.

Adoption of new products among social system is largely dependent upon the promotional effort imparted. The promotional effort in the form of advertising plays a pivotal role in the diffusion of products among the social systems. It has been observed that demand of the products and moreover new products largely depends upon the different kinds of advertising effects. Also, it is experienced that demand of new products is highly dynamic. Therefore, to keep pace with the dynamic behavior of demand of new products it becomes important to make strategy over the level of advertising expenditure. The paper describes an inventory model for new products where demand of the products varies with time under the external influence of dynamic advertising effects. The objective of the paper is to develop an optimal schedule of the inventory model for effective supply chain. To encounter with the uncertain environment a fuzzy technique has also been used wherein few parameters have been taken as fuzzy variables.

Mangala Oilfield of Rajasthan has produced over 36% of STOIIP and has been subjected to several innovative and new era technologies since it started producing in August’ 2009. Initially, field was under Water flood phase till April’2015 and then full field Polymer flood phase started to maximize recovery. Mangala field with medium-gravity viscous crude oil & formation water salinity of approximately 8000ppm has an excellent reservoir property of high porosity (24 to 26%), high permeability (200md- 20D) and very low irreducible saturation i.e., less than 5%. Thus, C/O logging in this field has been a very good choice to estimate the remaining oil saturation (ROS) and understand the sweep of oil due to injection which in turn has helped in maximizing recoveries from the field. Time-lapse PNL were run in several wells to monitor the efficacy of the water flood/polymer flood phase on oil recovery. The objective was two-fold; to estimate the change in saturation over time and to identify by-passed or marginally swept intervals. The process begins with recording the initial saturation in the wells before any production has occurred. Then time-lapse data are recorded to monitor the change in saturations. Secondly, saturation estimation from PNL data were used to plan the next course of action- workover operations, changing completion zones, abandoning certain zones or wells, and infill drillings. PNL data in combination with other reservoir surveillance techniques (MPLT) has proved to be a vital surveillance tool to maximize the recovery from this field. In this paper, we present the effectiveness of PNL tool specially RMT-I with production data over a period of 3 years (post Aug 2019). However, the results also include integration of other PNL dataset (RST & Raptor) acquired for reservoir surveillance activity and the challenges involved in interpreting the result of different PNL tool over time. In absence of RMT 3D tool, PNL is acquired as 1 Sigma up/down pass and 3 CO up passes at 1fpm-3fpm to address the uncertainty related to gas presence on C/O interpretation. Sigma measurement helped in identifying gas below packer or in the annulus behind pipe and helped in addressing the uncertainty related to gas presence on C/O interpretation. Secondly, RMT was planned in infill well post drill to determine the uncertainty between OH and Cased hole Oil saturation. The results agreed with production data and uncertainty in oil saturation estimation was minimized to 10-15% approximately. Several cases will be discussed in the paper to demonstrate the use of PNL logs for reservoir management.

This research study aims to examine the effectiveness of delivering a supply chain management course to students from a cross-functional perspective. The study analyses the positive teaching-learning outcomes that came out with the teaching of this course to the working professionals through online mode at an institution from a cross-functional perspective. The research question is whether teaching the supply chain management course from a cross-functional perspective resulted in better student performance in terms of Bloom's taxonomy. This study finds that the positive effect of this experiment is statistically significant on the treatment set. The study also proposes a few examples of cross-functional classroom teaching and linkages between different courses that need to be brought to the attention of the students. The study also sheds light on different tools of cross-functional teaching and how the management faculty can develop the art of delivering lectures from a cross-functional perspective, and the caution that they need to exercise while adopting this pedagogy style.

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.

The effective supply chain scheduling is a crucial task in business management which can be determined by developing the optimum schedules. Here, this paper develops the optimum schedules using an EOQ model with dynamic demand pattern because in this era of globalization and dynamic environment the Economic Order Quantity (EOQ) model loses its importance when it is based upon the constant demand pattern. Therefore, it becomes indispensable to develop the EOQ model under an environment of dynamic demand pattern. Here, the dynamic demand pattern includes the relevant parameters which varies with time. The effects of such parameters are necessary to incorporate in determining the optimum schedules and hence the optimum inventory levels. Also, to establish a product in the market and to increase its customer base one can take the help of promotional efforts in the form of trade credit financing. This paper discusses the optimum scheduling for a part of supply chain system using an EOQ model where the demand is dynamic varies with time and one of the promotional effort in the form of a two-stage trade credit is considered. The applicability of the model can be well understood through the sensitivity analysis of the parameters and its managerial implications.

Customer satisfaction is an important aspect of any commercial activity. It assumes greater importance in e-commerce due to the lack of personal contact between the buyer and the seller. Achieving higher customer satisfaction levels pose a challenge for e-commerce companies due to the increased spatial and temporal separation between companies and web consumers. The present study is to investigate the factors affecting customer satisfaction in e-commerce among online consumers in India. A survey was carried out on 643 online customers. Structural equation modelling was applied to check the extent to which the considered variables predicted customer satisfaction in e-commerce. The results determined drive for technology acceptance, service quality, trust and social influence as key predictors of customer satisfaction in e-commerce. The practical contribution of the study is for online vendors by giving an insight into the perception of online customers about technology acceptance, service quality, trust, social influence and customer satisfaction towards e-commerce. Such understanding may enable managers to adopt effective marketing strategies steps to deliver their services more efficiently by creating trust in the mind of customers.

Purpose This paper aims to assess the relationship between academic burnout-student engagement relationships on management students of the Delhi-NCR region of Northern India. It further attempts to study the moderating impact of internal locus of control and mediating impact of loneliness on the academic burnout-student engagement relationship. Design/methodology/approach The data was collected using standardized instruments from 264 respondents. Descriptive statistics, correlation and moderated-mediated regression analysis were used to test the hypotheses. Findings The study found a negative association between student engagement and academic burnout and loneliness. A positive association between academic burnout and loneliness and a moderating impact of internal locus of control on academic burnout and student engagement relationship. Loneliness acted as a partial mediator for the moderated relationship between the academic burnout-student engagement relationship. Research limitations/implications Sample size and sampling units are the limitations of the study. Practical implications The conclusion of the presented study offers different inferences including validating the self-determination theory (Ryan and Deci, 2000) and possible courses of actions to be taken by academic institutions and students themselves. It ranges from careful investigation of student’s behaviors, design and implements collaborative projects along with student’s involvement in social networking based groups for collaborations and help. Social implications With the help of the study, the society including parents, family, friends, officials and academicians at educational institutions can offer useful insights to students through recreational and social activities for behavior modifications. Originality/value The major contribution of the study is to understand the psyche of the budding professionals perceiving increased stress and pressure. Limited studies are found in the Indian context and no studies in the past have used the study variables together. Internal locus of control as a personality variable has not been studied with respect to student’s burnout and engagement. Furthermore, none of the studies done in the past have deliberated upon loneliness with respect to the student community.

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.

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.

One of the major concerns for the technology market is the demand volatility and its impact on inventory policies. Demand volatility in the technology sector may arise due to many factors namely customer choices, competition, growing market size, and so on. Often companies use rented warehouses to absorb any fluctuations in demand. Unfortunately, warehouse and inventory researches ignore the phenomenon of growing market size to formulate policy decisions. In this paper, we proposed a two-warehouse inventory model with deterioration for technology products with linearly increasing market size where demand follows innovation diffusion criterion. The model is based on the assumption that the holding costs in the rented warehouse are more than the own warehouse. A simple solution procedure also discussed to solve nonlinear cost function. Numerical example and sensitivity analysis are also used to describe the utility of the model.

The inventory management of new products becomes crucial because demand of such products is highly dynamic and has less predictable growth behavior. This is because there is strong relationship between nature of demand and procurement policy of the products. It becomes more significant when the concept of permissible delay in payments is also taken into account. There are numerous inventory models which do not incorporate the effect of permissible delay in payments which is unfortunate in the field of developing inventory models for new products. The permissible delay in payments is a kind of marketing tool which plays a significant role in influencing the demand of the products and it becomes more crucial when one discusses the inventory policies of new products. This paper discusses the economic ordering policies for new products where supplier offers trade credit period to the retailer and no interest is charged by the supplier to the retailer during this period. The concept of inflation and time value of money is also incorporated into the model. A solution procedure in the form of algorithm has been developed to solve the model numerically. A numerical example followed by comprehensive sensitivity analysis has been discussed to know the applicability of the model in the market.

Economic ordering policies for a retailer are often strategies subject to the nature of demand, and the kind of benefits received from the suppliers. Globalisation and continuum innovations of new products/technologies put enormous pressure on retailers to attract new customers and look after the current ones concurrently. Thus, a realistic economic order quantity (EOQ) model should link the present business requirements, which can enable the retailer to achieve its business objectives. Based on hazard rate demand, an integrated EOQ model is discussed in the paper for permissible delay in payments, under the assumption that supplier may offer credit periods to the retailer. The demand rate is assumed to be governed by the hazard rate function under dynamic pricing and advertising. The proposed framework is demonstrated with a numerical example and a comprehensive sensitivity analysis is also performed to validate effectiveness of the model.

Often, sales curve of a technology product exhibit a small peak and then decline, before continuing with the traditional bell shaped curve. Under this situation sales curve of the technology products show bimodal pattern. Traditional EOQ models have ignored the bimodal pattern of demand phenomenon during development of the policy frameworks. The approach in this paper is to study the effect of bimodal demand function, on economic order quantity model. Based on hazard rate demand, an integrated EOQ model is discussed in the paper for permissible delay in payments, under the assumption that supplier may offer credit periods to the retailer. The proposed framework is demonstrated with a numerical example and a comprehensive sensitivity analysis is also performed to validate effectiveness of the model.

Accurate prediction and knowledge of adoption pattern is critical to formulate inventory strategies for any technology product. Prior researches in this area recommended that aggregate level demand models often forecast imprecise sales figure. We argue that it is essential to recognize the technology specific adoption dynamics prior to formulate the inventory strategies. This paper aims to develop an Economic Order Quantity (EOQ) model to find strategy for a firm that sells technology products' over a defined planning horizon. Demand is considered to follow trial-repeat purchase phenomenon. The fuzzy criterion is incorporated to address the problems of uncertain nature of marketing parameters. The model is illustrated with a numerical example and a comprehensive sensitivity analysis on the optimal solution with respect to different parameters has also been performed.

In the present paper gives an algorithm to solution of systems of linear equations by finding the rank of coefficient matrix and rank of augmented matrix. Algorithm gives solutions of both types of equations Homogeneous system and Non Homogeneous system.

Marketing strategies such as advertising and pricing can play an important role in the acceptance of technology products by consumers. This phenomenon indicates that diffusion of technology products in the society may have strong linkages with unit selling price and advertisement effort. Therefore, management should sincerely reflect on pricing and advertising strategy during formulation of the inventory policies. This paper aims to develop an economic order quantity model for finding strategy for a firm that sells technology products' over a finite planning horizon. Demand is considered to follow a lifecycle phenomenon with dynamic ceiling on the potential adoptions and sensitive to advertising expenditure and unit selling price. The fuzzy criterion has also been incorporated to address the problems of uncertain nature of marketing parameters. The model is illustrated with a numerical example and a comprehensive sensitivity analysis of the optimal solution with respect to different parameters has also been performed.