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In the process of industrial growth, when existing industries go for technology upgradation and new modernised industries emerge, both capital intensity and energy demand of overall industry tend to rise steadily. This poses a serious challenge for sustainable development objectives. Towards this end, enhancing energy efficiency of individual industries is the only remedy. Against this backdrop, the study aims to probe the trends in capital intensities and energy efficiencies of individual industries in India.

This study uses panel data regression analysis on data of two-digit industries from 1980/1981–2016/2017. The statistical analysis includes relevant macroeconomic variables derived from the literature to ascertain the drivers of energy efficiency in industries.

The results brought out that capital deepening due to technology upgradation and modernisation and capital productivity growth are the decisive determinants of energy efficiency growth. Furthermore, the ever-increasing fuel price motivated industries to conserve energy on a steady basis, supplemented by energy conservation-specific policy interventions.

This study recommends policy initiatives to ascertain and address technology gaps industry-wise, so that its subsequent efficient capital utilisation, and energy conservation measures of industries would result in energy efficiency growth in industry. The policy must focus on energy-efficient capital intensification in fabricated metals, leather, textile and wood industries that are found less-energy-efficient despite being less-capital-intensive.

This study empirically explores the capital efficiency of industries by investigating the interaction between capital intensity and energy efficiency at a two-digit industry level. It explores the determinants of energy efficiency and proposes industry-specific policies for energy-efficiency-enhancement of the overall industry.

Technological start-ups are significant contributor to the innovation and employment provider in an economy. Numerous technological start-ups are established every year; however, only a miniscule percentage of these technological start-ups sustain and scale up in the long run. The aim of this study is to investigate the factors that affect Indian technological start-ups’ competitiveness.

Case study analysis of two technological start-ups (namely, WayCool and Moglix) is undertaken to study the factors affecting the competitiveness of technological start-ups in India. Being a relatively underexplored theme of study in entrepreneurship and strategy, case analysis facilitates exploration and validation of factors influencing competitiveness. Information for case study analysis is drawn from secondary sources of information. The collected data undergoes deductive thematic analysis to systematically identify and examine recurring themes and patterns relevant to the competitiveness of Indian technological start-ups.

Case analysis reveals that innovation intensity, organisational agility and internationalisation influence competitiveness of technological start-ups. The importance of the role of each of these factors for entrepreneurial ventures has been highlighted in literature; however, their effect on competitiveness has not been examined in extant literature.

Being among the few studies on the competitiveness of technological start-ups in specific and start-ups in general, this study highlights the gap in the literature and suggests the need for examining the competitiveness of technological start-ups.

For the practitioners, this study reinforces the need for entrepreneurs to emphasise fundamental factors that build competitiveness. Subsequently, the sources of competitiveness shall enable the start-up to gain a competitive advantage.

This is among the few studies to have explored the competitiveness of technological start-ups in the Indian context.

This paper aims to identify key factors influencing the development of advanced manufacturing clusters and propose governance pathways for their digital innovation ecosystems.

A quantitative analysis of the Tai-Xin Integrated Economic Zone in China is conducted using data collected through a questionnaire survey. An evaluation index for the development level of advanced manufacturing clusters is constructed, and a structural equation model is used to identify key influencing factors and governance pathways.

This paper reveals that factors such as industrial foundation, technological innovation capability, social institution environment and government policies have a significant positive impact on the development of digital innovation ecosystem in advanced manufacturing clusters. It constructs a governance model for the digital innovation ecosystem and proposes three major pathways: integration of heterogeneous innovation resources, enhancement of digital capabilities, and fostering digital collaborative governance. The crucial role of digital technology in improving data processing efficiency, optimizing resource allocation and promoting collaboration among entities is emphasized. These pathways can optimize resource allocation, boosting the competitiveness and innovation capacity of clusters.

By incorporating advanced manufacturing clusters into the digital innovation ecosystem framework, this paper enriches theoretical research on both fronts. It offers specific governance pathways and policy recommendations, providing valuable references and guidance for promoting the digital transformation and ecosystem construction of manufacturing clusters.

Housing is one of the basic necessities of humankind for survival and purchasing a home is often a substantial milestone. Individuals exhibit complex behaviour influenced by various factors while making decisions related to the purchase of residential properties. While most of the earlier studies have focused on understanding the purchasing behaviour of home buyers’ in developed countries, the research is limited on this topic in developing countries such as India. The booming information technology industry has rapidly increased the demand for residential properties among the migrant population in Bengaluru, India’s largest technology hub. Real estate developers strive to meet the requirements of prospective customers through innovative ways but face challenges in a competitive market.

It is essential to understand the factors influencing home buyers’ purchase attitudes for increasing property sales. However, a lack of research on this subject is identified in the emerging city of Bengaluru. This study aims to analyse the determinants of home buying decisions for potential investors in Bengaluru through structural equation modelling to provide insights for the real estate industry to construct houses as per their customers’ needs.

It was found that housing amenities, financial aspects, location conveniences and marketing services significantly influenced home buyers’ purchase decisions, whereas housing features do not.

The findings of this study offer valuable insights for governmental bodies to implement appropriate policies and for builders to design properties with features that cater to the target population, thereby promoting sustainable growth in the real estate industry.

This study aims to investigate how Lean Six Sigma (LSS), a widely used paradigm that promotes competitive advantage of different organisations in a more sustainable and environmentally friendly way, affects operational performance in different organisational contexts. Although LSS is widely used to improve operational performance, the impact of LSS on operational performance appears to be different in different organisational contexts, prompting the attention of researchers and managers to shift from lean philosophy to the impact of contextual variables on the effectiveness of LSS implementation.

This study uses a quantitative research design and conducts an empirical study in Pakistan. The sample consists of 339 management employees with an effective response rate of 67.8% in various sectors. In this study, partial least square structural equation modelling is used to examine the relationships among the variables using the resource-based view (RBV) and dynamic capability theory (DCT) to support the model of this study.

This study reveals that the relationship between LSS and operational performance is partially mediated by green human resource management (GHRM) and internal environmental management (IEM). The moderating effect of the organisational developmental culture between LSS and operational performance is not identified, implying that the effect of developmental culture could vary under different cultures.

There is a lack of empirical studies investigating the role of GHRM, IEM and developmental culture in developing countries. This study extends the literature on the RBV and DCT in operational performance. The study’s outcome provides theoretical and practical implications for enhancing the effect of LSS implementation on operational performance in focal small and medium-sized enterprises (SMEs) through human and environmental management factors.