Rohit Nishant

Energy efficiency benefits: is technophilic optimism justified?

Despite the increased focus on making energy more efficient, research has rarely examined the temporal impact of energy efficiency on environmental performance at the national level. Using archival data, we conduct an econometric analysis that provides empirical evidence indicating the negative effects of the rebound effect and the positive effects of technology. Our results suggest that an increase in per capita energy consumption does not lead to an increase in emissions, but it could negate the environmental benefits arising from energy efficiency. However, energy efficiency leads to an increase in per capita emissions for developed countries. Post hoc results show that energy efficiency influences the three sectors (household, services, and industrial) differently on per capita energy consumption and emissions. Implications for research and practice are discussed.

Do shareholders favor business analytics announcements

Abstract Despite the growing acceptance of business analytics (BA) as a tool for making smarter business decisions, past research has rarely investigated shareholder reactions to BA announcements. We use signaling theory and resource-based theory (RBT) as our theoretical lens. The results show that BA announcements generate positive abnormal returns, thereby providing empirical evidence that shareholders view BA as beneficial. The results also suggest that characteristics that are more salient to shareholders are rewarded. Specifically, firms implementing BA systems from market-leading vendors obtain more positive stock market reactions compared with other firms. Announcements convey more benefits to overbought stocks than oversold stocks, and generate higher positive return in firms with high sales growth and high return on assets (ROA). Overall, empirical evidence favors signaling theory over RBT.

Disentangling Environment-Specific Sustainability-Oriented Innovation: Insights from the Airbus-Boeing Duopoly

We develop an empirically grounded understanding of Environment-Specific Sustainability-Oriented Innovation (ES-SOI) in the technology-intensive aviation sector. Focusing on the Boeing-Airbus duopoly, we use secondary and archival data from several sources (e.g., sustainability reports and databases). Methodologically, manual coding and centering resonance analysis (CRA) based clustering techniques are used to arrive at distinct types of ES-SOI. Specifically, resource consumption and resource efficiency are salient in the ES-SOI. We conclude with how these distinct ES-SOIs could extend theoretical deliberations on the SOI.

Food for Thought: Managing Secondary Data for Research

Social science researchers are strongly motivated to understand the world of business and its associated phenomena. In contrast to pure science research, social science studies combine strong narratives with empirical or analytical investigation. Such research is enticing, invigorating, and essential in current academic and practitioner domains, but each aspect is challenging and resembles a maze. Researchers must navigate diverse paths to identify appropriate theory, concepts, data sources, and knowledge for analysing and understanding social science phenomena. In this chapter, the authors explore new sources of data and the challenges of using them. Drawing upon personal experiences, as empirical researchers, the authors make recommendations about the use of secondary data.