Indian Institute of Management Bangalore

About: Indian Institute of Management Bangalore is a education organization based out in Bengaluru, Karnataka, India. It is known for research contribution in the topics: Emerging markets & Corporate governance. The organization has 491 authors who have published 1254 publications receiving 23853 citations. The organization is also known as: IIMB.

How prosocial is proactive: Developing and validating a scale and process model of knowledge-based proactive helping

Abstract: The knowledge exchanges literature considered all types of knowledge exchanges as reactive. The present study develops the conceptual framework and the measure of knowledge-based proactive helping that was missing in earlier literature. The measure was validated across multiple population. Proactive helping was manifested in the scale items effectively, to the extent that at first, initially chosen five dimensions merged to form two factors: professional development and problem mitigation and; subsequent analysis revealed that the factors represented the same underlying construct of proactive helping. The nomological network, a process model highlighting the psychosocial causes and benefits of proactive helping based upon social exchange theory and social motivation theory was also proposed. The significance of the study was in bringing the prosocial, proactive exchanges at the forefront of knowledge exchanges, which predominantly focussed on reactive exchanges.

Performance evaluation of closed tree-structured assembly systems

Abstract: Assembly systems are very common in manufacturing environments. In such systems, certain machines require more than one part type before they can start processing. Our paper presents a practical stochastic model for evaluating the performance of closed-loop assembly systems. This evaluation is difficult because of synchronization delays and the large state space required to capture the interaction of the flow of parts among the various subassemblies. We present an approximate, but computationally efficient, aggregation/disaggregation algorithm to compute the system throughput and mean queue lengths for both the matched and unmatched WIP inventory components. The aggregation computes the conditional system throughput as a function of the number of jobs in the system, whereas the mean queue lengths are obtained by disaggregation. Application of our algorithm reveals several salient operational insights, such as the increase in queue length towards the downstream machines or the concavity of the assembly sys...

Interdependence between experience marketing and business strategy

Abstract: Purpose – The extant literature on experience marketing takes a narrow functional approach engaging with issues like defining an experience brand and recommending strategies for creating a unique customer experience. The purpose of this research is to focus on the cross‐level interdependencies in the organization and examine interrelatedness between business strategy and experience marketing.Design/methodology/approach – Drawing on the extant literature on business strategy and experience marketing and investigating an in‐depth case study on experience marketing this article arrives at strategic principles of experience marketing. It uses an in depth analysis of a case study of an experience hotel brand covering multiple facets of its business strategy in all its complexities. Data were collected from six sources of evidence: documents, archival records, interviews, direct observation, participant‐observation and physical artifacts. A total of 17 interviews lasting from one to several hours each were cond...

Evidence on Community-Driven Development from an Indian Village

Abstract: This article examines the functioning of a community-driven development (CDD) project that, unlike most CDDs, was set in a homogeneous community, consisted of simple tasks, had a year-long pre-inte...

Analyzing airlines stock price volatility during COVID-19 pandemic through internet search data

Abstract: Recent Coronavirus pandemic has prompted many regulations which are affecting the stock market Especially because of lockdown policies across the world, the airlines industry is suffering We analyse the stock price movements of three major airlines companies using a new approach which leverages a measure of internet concern on different topics In this approach, Twitter data and Google Trends are used to create a set of predictors which then leads to an appropriately modified GARCH model In the analysis, first we show that the ongoing pandemic has an unprecedented severe effect Then, the proposed model is used to analyse and forecast stock price volatility of the airlines companies The findings establish that our approach can successfully use the effects of internet concern for different topics on the movement of stock price index and provide good forecasting accuracy Model confidence set (MCS) procedure further shows that the short-term volatility forecasts are more accurate for this method than other candidate models Thus, it can be used to understand the stock market during a pandemic in a better way Further, the proposed approach is attractive and flexible, and can be extended to other related problems as well