One foot in the city, one in the village: India’s urban poor and their rural bonds

When many of India’s poor move from their rural homes to the country’s packed cities, they remain registered in their village. Here Ankush Agrawal (Indian Institute of Technology Delhi) and Vikas Kumar (Azim Premji University, Bengaluru) explain the reasons why India’s urban poor keep a foot in villages and its policy consequences

Improved Kerogen Models for Determining Thermal Maturity and Hydrocarbon Potential of Shale

Kerogen is the insoluble component of organic-rich shales that controls the type and amount of hydrocarbons generated in conventional and unconventional reservoirs. Significant progress has recently been made in developing structural models of kerogen. However, there is still a large gap in understanding the evolution of the molecular components of kerogen with thermal maturation and their hydrocarbon (HC) generative potential. Here, we determine the variations in different molecular fragments of kerogen from a Marcellus Shale maturity series (with VRo ranging from 0.8 to 3) using quantitative 13C MultiCP/MAS NMR and MultiCP NMR/DD (dipolar dephasing). These molecular variations provide insight into the (1) evolution of the molecular structure of kerogen with increasing thermal maturity and, (2) the primary molecular contributors to HC generation. Our results also indicate that old model equations based on structural parameters of kerogen underestimate the thermal maturity and overestimate the HC generation potential of Marcellus Shale samples. This could primarily be due to the fact that the kerogen samples used to reconstruct old models were mostly derived from immature shales (VRo \u3c1) acquired from different basins with varying depositional environments. We utilized the kerogen molecular parameters determined from the Marcellus maturity series samples to develop improved models for determining thermal maturity and HC potential of Marcellus Shale. The models generated in this study could also potentially be applied to other shales of similar maturity range and paleo-depositional environments

A New In-Store Digital Landscape: Effect on Engagement, Innovativeness, and Unplanned Grocery Shopping Outcomes

Digital technologies are having a profound effect on the path to purchase in a grocery retail environment. Secondary research data on shopping habits is used to analyze the relationship of consumer digital technology use, a consumer’s innovativeness, and consumer engagement with unplanned grocery shopping behavior within a grocery store environment. Findings indicate that all of three variables have a direct, significant effect on unplanned grocery shopping outcomes and that innovativeness has a direct effect on engagement. Future study will consider the impact of key market segments, shopping situations and digital technology types

Enabling Knowledge Sharing Through Intrinsic Motivation And Perceived IT Support

Knowledge is currently viewed as a key organizational resource to gain and sustain competitive advantage. Having the right knowledge at the right time to take effective action has become ever more critical for organizations. A key aspect of achieving this is by promoting conditions that enable organizational members to share their knowledge in the most effective manner. This research investigates the impact of knowledge workers’ intrinsic motivation and their perceived usefulness of information technology support on knowledge sharing. The proposed model is tested using data from a sample of 252 knowledge workers in manufacturing and related industries. Results support proposed hypotheses suggesting that knowledge workers intrinsic motivation and perception of usefulness of information technology support positively affects knowledge sharing. Intrinsic motivation also affects knowledge sharing indirectly by enhancing knowledge workers’ perception of information technology they use to share knowledge. This research underscores the importance of individual characteristics such as motivation and employee perception in sharing knowledge

Linking Information Sharing And Supplier Network Responsiveness With Delivery Dependability Of A Firm

The twenty first century organization is required to provide accurate on time deliveries in addition to providing high quality products at low costs. This can be achieved if various processes within and between the organizations are streamlined and well defined. Several studies have indicated the significance of various manufacturing (or internal) practices that are instrumental in creating time-based competitive capability. Collaborative relations and information sharing practices with suppliers have long been believed to positively impact the responsiveness and delivery performance of organizations and supply chains. Responsive suppliers can play a key role in affecting a firm’s own delivery performance.  This research investigates and tests the relationships between information sharing practices of a firm, supplier network responsiveness, and delivery dependability of a firm. The large scale web-based survey yielded 294 responses from industry professionals in the manufacturing and supply chain area. The proposed relationships were tested using structural equation modeling. The research findings point out that higher level of information sharing practices can lead to improved supplier network responsiveness, and higher levels of supplier network responsiveness can have a direct positive impact on delivery dependability of a firm. The implications of our findings are discussed and directions for future research are provided

The New In-Store Consumer: Digital, Engagement, Innovativeness Impact on Unplanned Grocery Shopping and Spending Behavior

Digital technologies are having a profound effect on the grocery retail environment worldwide. Marketers have been intrigued by potential for digital technologies to influence consumers at the point of purchase, yet little is known about how digital technologies impact consumer purchasing decisions. An exploratory PLS-SEM model is used to analyze U. S. panel data and the effect of in-store digital use, consumer innovativeness and engagement on unplanned grocery shopping behavior and spending. This study finds that consumer engagement, rather than in-store digital use, is found to be the key variable when it comes to predicting unplanned shopping and spending. Findings identify an ancillary role for in-store digital use as it directly affects engagement and indirectly affects unplanned shopping and spending. Finally, this study finds that gender moderates the relationship of innovativeness and digital use, digital use and engagement, and digital use and total spending. As a result, the effects of consumer engagement and in-store digital use on unplanned purchase behavior have been clarified

A bi-criteria evolutionary algorithm for a constrained multi-depot vehicle routing problem

Most research about the vehicle routing problem (VRP) does not collectively address many of the constraints that real-world transportation companies have regarding route assignments. Consequently, our primary objective is to explore solutions for real-world VRPs with a heterogeneous fleet of vehicles, multi-depot subcontractors (drivers), and pickup/delivery time window and location constraints. We use a nested bi-criteria genetic algorithm (GA) to minimize the total time to complete all jobs with the fewest number of route drivers. Our model will explore the issue of weighting the objectives (total time vs. number of drivers) and provide Pareto front solutions that can be used to make decisions on a case-by-case basis. Three different real-world data sets were used to compare the results of our GA vs. transportation field experts’ job assignments. For the three data sets, all 21 Pareto efficient solutions yielded improved overall job completion times. In 57 % (12/21) of the cases, the Pareto efficient solutions also utilized fewer drivers than the field experts’ job allocation strategies

Simulation Model and Analysis of a Data Warehouse

Data warehouses are large complex systems with many interacting nonlinear components. It is an amalgamation of many different systems and integration of such diverse elements is its primary concern. It is often difficult for a data warehouse manager to predict the performance of the system especially when demand pattern for the required data keeps changing. We have developed a simulation model using ARENA simulation package that will simulate the behavior and performance of a data warehouse system environment based on its overall design. Given such a model, a data warehouse manager can walk through various what-if scenarios and can pinpoint the areas of weaknesses in the system. This visibility could result in improved operational performance in a data warehouse

Notes on Nagaland’s area

Empirical research in economics and, to a lesser extent, in other social sciences is largely dependent upon government statistics. It is generally assumed that governments are committed to collecting and disseminating correct statistics. As a result, the mutually constitutive relationship between politics, economy, and statistics, and the possibility of systematic manipulation of statistics driven by the structural features of this relationship, has received insuf�icient attention within economics. This paper examines the implications of the absence of shared preferences over the quality of statistics within a government. It explores the multiplicity of con�licting maps of the State of Nagaland issued by different tiers and wings of the government to underscore the lack of attention paid to a statistic as crucial as area. The paper situates the cartographic-statistical confusion in its political and economic contexts, and suggeststhat political-geographic arguments are being used to advance political-economic interests along contested borders. It argues that the confusion is not amenable to a technical resolution as it islinked to the dispute over Nagaland’s place within the Union of India and the border disputes between Nagaland and its neighbouring states

Infirmities in NSSO data for Nagaland

The samples of the National Sample Survey Office are unlikely to be representative of Nagaland. This is so not because of the size of the sample, but because of the arbitrary restriction to villages within 5 kms of bus routes, whereas the bulk of the rural and tribal population is located farther from the roads. Further, it is argued that the Census of India data, which is used as the sampling frame, is found to be unreliable for Nagaland