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This study examines the relationship between servant leadership and its dimensions on firm performance, with big data playing the role of a mediator.

Survey responses used for analysis in this study have been taken from business managers associated reputed private sector organizations in India. A conceptual model is proposed grounded to the Conservation of Resource Theory (COR). Structural equation modeling has been used to test the proposed model.

Servant leadership significantly relates to firm performance, whereby Big Data is seen to play the role of a mediator. The results also indicate that none of the dimensions of servant leadership independently affect firm performance.

The study adds to extant research by examining the mediating mechanism of Big Data in servant leadership and firm performance. It also suggests that each dimension of servant leadership gets reflected in overall servant leadership. Here it is important to note that Big Data analytics partially mediate the effectiveness of servant leadership.

Housing market is predominantly driven by supply and demand, and the measurement of housing supply plays a crucial role in understanding market dynamics. One such measure is the number of building permits (BPs) issued. Despite the importance of BPs as an economic indicator, direct links have yet to be drawn between BP and housing value index (HVI). The purpose of this paper is to establish links between HVI and BP.

Trials were conducted using data at the national, state and metropolitan statistical area (MSA) levels. For each trial, the Granger causality test was used first to identify causal relationships between HVI and BP. Subsequently, the vector autoregression model was implemented in an attempt to observe impulse–response relationships and to create a forecast for HVI.

Bidirectional causal relationships were observed between HVI and BP at the national, state and MSA levels. The number of issued BPs proves to be an indicator for HVI. Impulse response functions indicate that HVI responds negatively to an increase in BP in the short term of 4–7 months but positively to an increase in BP with a lag of 10–12 months.

To the best of the authors’ knowledge, this paper is the first in the body of knowledge that establishes the number of issued BPs as an indicator for housing value. The results drawn using impulse–response function are also novel and had not been observed in previous studies.