School of Management & Entrepreneurship

&ldquo;IIT Jodhpur is committed to impart quality education to facilitate the creation of qualified, competent and responsible human resources to meet the emerging technological challenges of the world. It is working towards creating an equitable learning platform that is positive, accessible and effective in the face of the modern societal and scientific advancements.

Flexibility in curriculum, in all its academic programs, encompassing elements of teaching, research, creativity, innovation and entrepreneurship is the most unique feature of IIT Jodhpur. The Department of Science and Technology (DST), under the National Mission on Cyber Physical Systems, has identified IIT Jodhpur as a Technology &amp; Innovation Hub in the area of Augmented Reality and Virtual Reality. The institute has also been nominated as the coordinator for the Jodhpur City and Knowledge Cluster by the Office of Principal Scientific Adviser, Government of India.

The sprawling 852-acre IIT Jodhpur campus is a majestic tribute to the deep-rooted diverse cultural heritage of the region. The campus is an architectural masterpiece, which is slated to become an international exemplar of sustainability with net-zero energy, and advanced water and waste management strategies.&rdquo;

IIT Jodhpur

Purpose: The purpose of this study is to propose an integrated framework utilizing the theory of planned behaviour (TPB) and technology acceptance model (TAM) to augment the understanding on consumers’ showrooming behaviour. Design/methodology/approach: Selective sampling was used for data collection. The integrated TAM-TPB framework led to 12 propositions, which were tested using partial least squares-structural equation modelling. Findings: Both perceived relative search benefits offline and relative purchase benefits online significantly determined the consumers’ showrooming behaviour along with perceived ease purchasing online and the overall usefulness of the showrooming sequence. Results of the study revealed that the showrooming sequence helped consumers avoid the regret of making suboptimal product choices and paying a higher price for the same product. Online trust was found to partially mediate the relationship between consumers’ intention to showrooming and the actual showrooming behaviour. Research limitations/implications: Notwithstanding the fact that further research is required to arrive at definitive conclusions, this study is an initial move towards understanding the consumers’ showrooming behaviour, and the research provides meaningful insights. Practical implications: As showrooming substantially erodes profits, devising strategies to defend showrooming customers becomes crucial. The findings of the study provide the basis for formulating strategies to counter showrooming customers. Originality/value: The paper is amongst the first studies which helps enhance the understanding of consumers’ showrooming behaviour, which is an emerging area in the present multi-channel retailing environment. © 2018, Emerald Publishing Limited.

World University root node

Journal of Consumer Marketing

Antecedents to consumers' showrooming behaviour: An integrated TAM-TPB framework

With the advent of technology, a greater amount of information is available in a greater variety of formats that are accessible through a greater variety of media and communication channels, resulting in a much more complex and rich information environment for business managers. Many businesses are seeing the development of big data as unique opportunity and also experience it as demanding in terms of managerial skills and organisational capability to deal with it. Existing literature provides managerial prescriptions and systemic guidelines to make use of this information, but does not provide empirical evidence on how practising managers actually deal with information overload and make sense of the available data. This article discusses the findings from an interpretive case study of five organisations from the hotel industry within the hospitality sector. It was found that the volume and pace coupled with the qualitative and unsolicited nature of information caused information overload to managers. To cope with this phenomenon at personal level, managers used a combination of filtering, withdrawal and summarising strategies. At organisational level, the practice of summarising evolved into development and use of interactive dashboards. © The Author(s) 2018.

Journal of Information Science

Information overload and coping strategies in the big data context: Evidence from the hospitality sector

Demonetization initiative by Govt. of India in Nov-Dec, 2016 aimed at addressing the issues like black money, hoarding and overall Dcleansing the monetary system. This paper in this regard attempts to empirically examine the impact of demonetization drive upon the monetary system by taking data of 180 days prior to Nov, 2016. The cointegration results exhibit show a long run cointegration between the money supply, demonetization dummy, cash in hand, notes in circulation and bank deposits. Furthermore, our Bayer-Hanck cointegration also confirms the cointegration among the variables. Our error correction mechanism analysis shows the long run relation between the variables. The variance decomposition analysis further states that effect of demonetization is widely visible upon the cash in hand followed by the notes in circulation. Despite the wider claims by the government regarding the positive impacts of demonetization drive, this initiative is fraught with several challenges and limitations. The implications of this initiative are discussed in this paper. © 2018, University of Teheran. All rights reserved.

Iranian Economic Review

An empirical insight of examining impact of recent demonetization on monetary system: Evidence from India

This article investigates commonality in liquidity on India's National Stock Exchange (NSE) using high frequency limit order book data. The analysis pertains to 50 mid-cap stocks for the period April–July 2015. A comprehensive record of more than 100 million orders and trades is aggregated at 30 min intervals to construct a variety of spread and depth measures of liquidity. The empirical analysis shows that individual stock liquidity co-moves to a high degree with market liquidity and industry liquidity. Market-wide commonality is found to be stronger than industry-wide commonality for most liquidity measures. Commonality is further found to be greater in heavy manufacturing than in consumer goods, financial services, or infrastructure sectors. For most stocks, up markets show a stronger degree of commonality than down markets. Finally, short-run commonality is found to exceed long-run commonality, which suggests greater presence of noise traders in short run. © 2018 Elsevier Inc.

Journal of Asian Economics

Commonality in liquidity: Evidence from India's National Stock Exchange

Purpose: This research aims to explore the factors that affect the adoption of Web 2.0 among knowledge workers. The research specifically investigated the role of factors related to both knowledge seeking and knowledge sharing, in the context of Web 2.0 use by health care professionals. Design/methodology/approach: For this research, a cross-sectional survey design was adopted. The data were analyzed using the partial least square-structural equation modeling. Findings: The results confirmed that the intention to adopt Web 2.0 depends upon both the knowledge-seeking and the knowledge-sharing attitudes. However, between the two, it is knowledge-sharing factors that are more important. Health care professionals tend to share knowledge driven by intrinsic motivators rather than by extrinsic motivators. On the other hand, knowledge-seeking attitude was determined by usefulness of knowledge and was not affected by the effort involved. Research limitations/implications: All the respondents were health care professionals from India and convenience sampling was used to reach them. This may limit the generalizability of the findings. Practical implications: This research provides useful insights on implementing Web 2.0-based knowledge management systems, specifically for health care professionals. Particularly, it emphasizes the need to focus on reinforcing intrinsic motivators like self-efficacy and the joy of sharing. Originality/value: It is perhaps the first study that integrates the factors related to knowledge sharing and seeking in a single theoretical model, thereby presents and tests a more realistic model of knowledge management.

Journal of Knowledge Management

Factors affecting Web 2.0 adoption: exploring the knowledge sharing and knowledge seeking aspects in health care professionals

This paper presents an engineering informatics based approach to identify and assimilate effective and widely used parameters which are considered in literature in formulating synchronizer models. A methodology is proposed here to determine the optimal values of the selected parameters for improving the gear synchronization time. The synchronization mechanism is a major component of the transmission system that aids to a smooth gear shifting. Recent trends in gear synchronization efficiency improvement reveals that there is a challenge in improving the synchronizer mechanism for achieving quick and energy efficient transmission. A simulation study, formulated as a block model, for computation has been carried out in a reliable software environment like MATLAB with input parameters namely, the moment of inertia of engine, transmission input inertia, cone angle and coefficient of friction of the sleeve throughout. Lower synchronization time is desirable and hence, it has been considered here as the output parameter in the simulation modelling for computation with respect to the input parameters. A parametric optimization utilizing Response Surface Methodology (RSM) based data, obtained from the computational model and data analysis, has been conducted to determine the optimal parameter values for realizing robust design with minimization of synchronization time as objective function. Furthermore, the interactions of the individual input parameters with the output parameter namely, synchronization time has also been observed. Such observations help in understanding the effectiveness of the parameters associated with synchronizer design to improve the product quality for synchronizer manufacturing. © 2018, Curran Associates Inc. All rights reserved.

Proceedings of International Conference on Computers and Industrial Engineering, CIE

Response surface methodology based engineering informatics with a case on optimal shifting time in automotive gear synchronizers

Sequential estimation is a well recognized approach to inference in statistical theory. In sequential estimation the sample size to use is not specified at the start of the study, and instead study outcomes are used to evaluate a predefined stopping rule, if sampling should continue or stop. In this article we develop a general theory for sequential estimation procedure for constructing a narrow confidence interval for a general class of effect sizes with a specified level of confidence (e.g., 95%) and a specified upper bound on the confidence interval width. Our method does not require prespecified, yet usually unknowable, population values of certain parameters for certain types of distributions, thus offering advantages compared to commonly used approaches to sample size planning. Importantly, we make our developments in a distribution-free environment and thus do not make untenable assumptions about the population from which observations are sampled. Our work is thus very general, timely due to the interest in effect sizes, and has wide applicability in the context of estimation of a general class of effect sizes. © 2017 American Psychological Association.

Psychological Methods

Accuracy in parameter estimation for a general class of effect sizes: A sequential approach

There is presently no instrumentation that can provide (near) real time information on elemental composition of atmospheric aerosols. We describe an arrangement where air is sampled through a cyclone @30 L/min with a 50% cutoff @ ~250 nm. The particles deposit into a cup through which deionized water is continuously flowing. High purity HNO3 is added downstream and the mixed stream optionally flows through a quartz photo reactor (185 nm, ~90 °C, tR ~1.2 min) and is aspirated by an induction coupled plasma mass spectrometer (ICP-MS). Comparative batch experiments in which samples were not photodigested at all or thermally digested off-line for an extended period indicated no statistically significant difference in the results. This observation agrees with early theoretical and experimental work. Some 22 elements were quantifiable (S/N &gt; 10) at all times in the aerosol samples collected in our highly urban sampling location; an additional 4 elements were quantifiable at times of construction activity in the general area. Presently attained system limits of detection (LODs) are orders of magnitude higher than the instrumental LOD, both because of the purity of the acid and pump-induced contamination. These aspects can be vastly improved and will need to be improved to determine background concentrations. © 2017 Elsevier B.V.

Talanta

Continuous measurement of elemental composition of ambient aerosol by induction-coupled plasma mass spectrometry

This study examines the relationship between urbanization, energy consumption, foreign direct investment (FDI), and carbon dioxide (CO2) emission of 17 countries in the South and Southeast Asian (SSEA) region during the period 1980–2012. In order to find out the intensity of CO2 emission in 17 countries, we classify the total sample countries into three sub-groups, namely high, middle, and low-income countries. These three sub-panels are constructed based on their gross national income per capita of countries. Pedroni cointegration result shows that urbanization; primary energy consumption, FDI, and CO2 emission are cointegrated in all sub-groups of countries, regardless of their levels of national income per capita. Furthermore, while incorporating the fossil fuel energy consumption in place of primary energy consumption in the alternative specification of regression, the result suggests a cointegrating relationship between fossil fuel energy consumption, FDI, urbanization, and CO2 emission in middle-income countries. Nevertheless, Westerlund cointegration results are more or less in the line of Pedroni results. Furthermore, the results reveal that primary energy consumption, fossil fuel energy consumption, and FDI are substantially affecting the CO2 emission in the SSEA region. Moreover, the empirical findings suggest that in middle-income countries, both primary and fossil fuel energy consumption are considerably increasing the CO2 emission, and leading to greenhouse gas problem in the SSEA region. © 2016 Elsevier Ltd

Renewable and Sustainable Energy Reviews

The effect of urbanization, energy consumption, and foreign direct investment on the carbon dioxide emission in the SSEA (South and Southeast Asian) region