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The contemporary business environment is characterised by an increasing reliance on artificial intelligence, automation, optimisation, efficient communication and data-driven decision making. Based on the limited academic literature that examines the managerial perspective on enterprise chatbots, the paper aims to explore organisational needs and expectations for enterprise chatbots from a managerial perspective, assesses the relationship between managerial knowledge and managerial opinion regarding enterprise chatbots, and delivers a framework for integrating chatbots into the digital workforce.

The paper presents a quantitative design. An online, self-administered survey yielded 111 valid responses from managers in service and manufacturing organisations based on convenience and snowball sampling strategies. Given the nature of the data and the research questions, the research was conducted using principal component analysis, parallel analysis, correlation, internal consistency and difference in means tests.

This research explores the managerial perspective on enterprise chatbots from multiple perspectives (i.e., adoption, suitability, development requirements, benefits, barriers, performance and implications), presents a heat map of the average level of chatbot need across industries and business units, highlights the urgent need for education and training initiatives targeted at decision makers, and provides a strategic framework for successful chatbot implementation.

This study equips managers and practitioners dealing with enterprise chatbots with knowledge to effectively leverage the expected benefits of investing in this technology for their organisations. It offers direction for developers in designing chatbots that align with organisational expectations, capabilities and skills.

Insights for managers, researchers and chatbot developers are provided. The work complements the few academic studies that examine enterprise chatbots from a managerial perspective and enriches related commercial studies with more rigourous statistical analysis. The paper contributes to the ongoing discourse on decision-making in the context of technology development, integration and education.

This paper investigates how relative environmental regulation influences the flow of foreign direct investment (FDI), and thereby assesses the pollution haven hypothesis (PHH). In this field, conflicting results exist, partly due to the mere consideration of absolute environmental regulation or the inadequate consideration of endogeneity. Concerning these, we study China’s inward FDI from 26 developed countries and 12 developing countries over 1996–2009, and collect four different environmental regulation indicators at relative values of CO₂, SO₂, PM10, and an environmental regulation index. Using an instrumental variable approach, we find strong PHH evidence no matter for the subsample of FDI from developed countries or the one from developing countries. Moreover, we show how such results can be masked if failing to consider the endogeneity.

Higher economic output as measured in gross national product (GNP) may not always imply a higher quality of living. It has been the outcome of the long debate between growth and development of a nation. The aims of economic growth should be reconsidered because it has polluted the environment, wasted natural resources, harmed people’s quality of life, and failed to alleviate socioeconomic problems. It is also a common phenomenon to the economies of the South Asian region. The study is thus conducted to show the existence of long-run relationship and short-run interplays between output efficiency of energy use (GEU) and carbon efficiency of energy use (CEU) in the panel of countries in the South Asian region for the period of 1971–2014. The results show that there is a long-run and short-run association between energy efficiency in output and carbon emission as respectively measured in GEU and CEU. This means that in South Asia, energy consumption leads to an increase in both gross domestic product and carbon emissions. When GEU is used as the independent variable in vector error correction model (VECM), the result reveals that any short-run disequilibrium from the long-run stable connection will be adjusted over time, and the long-run stable relationship will be restored.

Using the Environmental Kuznets Curve (EKC) hypothesis as a theoretical framework and applying Estimated Generalised Least Square (EGLS) approach, this chapter examines the impact of energy consumption, economic growth, industrialisation and corruption on carbon dioxide emissions as well as finds out the causal relationship among them using panel data of 10 Asian economies over the period 1980–2019. Our empirical findings from EGLS model suggest that there exists an ongoing rising relationship between CO₂ emissions and economic growth both in the short-run and long-run which is opposing to what is claimed by the EKC hypothesis. Moreover, per capita CO₂ emissions rise positively with respect to increase in energy consumption, urbanisation, gradual industrialisation and growth in urban population in the long-run. Moreover, countries with adoption of more corruptive practices are found to have causing more environmental degradation through excessive emission of carbon dioxide in the long-run. The study also indicates the existence of unidirectional causalities running from carbon dioxide emission to energy consumption, from industrialisation and urban population growth to per capita CO₂ emissions, from industrialisation to GDP growth per capita and bidirectional causality between financial development and economic growth via GDP growth per capita. Therefore, these unidirectional causalities entail that CO₂ emission reduction or abatement measures can be applied without having any unpleasant effect on the real industrialisation, energy consumption and urbanisation in selected Asian countries.

Air pollution affects labour productivity and these effects arise in both indoor and outdoor environments and at varying levels of worker skill. They also arise at levels of air pollution generally considered to be within existing air quality standards and guidelines. Although the damage per individual is small when compared to more extreme events, such as mortality and hospitalisations, the effects are more widespread and may thus represent a significant cost to society. Labour is an essential element in every nation’s economy serving as one of the primary factors of production and India not an exception. Investing in human capital is viewed as a key source of sustained increase in labour productivity and economic growth. On the other hand, environmental regulations are typically considered to be a struggle on the economy. However, improved environmental quality may actually enhance productivity by creating a healthier workforce. At the same time, air pollution may affect labour productivity and can reduce the productivity of workers in physically demanding occupations. This chapter may be an attempt to provide comprehensive estimates of the major air pollutants in different states of India and also tries to identify the linkage between air pollution and labour productivity in case of Indian manufacturing sector.

It is a well-known fact that economic development and rise in the volume of trade due to globalization have led to more production which has further led to the increase in the emission of carbon dioxide in the environment. Under the backdrop, the aim of this chapter is to examine the relationships among per capita CO₂ emissions as the proxy for exploitation of the environment with international trade and per capita GDP in India. It analyzed cointegration and short-run causal relationships between the variables based on a time series data set for the period of 1979–2018. The data found to be stationary at first integration; hence the researchers ran cointegration. The study found that the carbon emissions are an outcome of economic growth and more and more trade with the foreign countries.

More than 30 legal recyclables were proclaimed by Environmental Protection Administration (EPA) in Taiwan of those producers and importers are liable for paying a Resource Recycling Fee (RRF). The Resource Recycling Management Fund determines both the tariff of RRF and the subsidy rate for recycling activities based on a predetermined pricing formula and collects the revenue to finance its collection and disposal. While contemplating on whether to proclaim waste mattress as a legal recyclable, EPA is facing several critical challenges, particularly the lack of data required for setting a tariff–subsidy mix. In this chapter we critically review the formula and propose an innovative pricing rule. Also, we develop a science-based approach to demonstrate how a tariff–subsidy mix could be determined under the circumstance of data deficiency. By doing so, we avoid not only the difficulty in solving the nonhomogeneous and nonautonomous first-order difference equation that governs the stock accumulation of waste mattress but also the distributed lag model of multiperiods linking quantity of mattress discarded and the quantity of new mattress sold. Such an approach could be applied to the durables for recycling pricing particularly when relevant data are limited.

This study aims to explore twin objectives. Initially, the study scrutinises the consequences of various pollution control acts and protocols signed by India to improve the air quality and then the study involves itself to investigate the aftermath of COVID-19 lockdown on the air quality of highly populated Mumbai city of India. The empirical analysis is facilitated by the application of Poirier’s Spline function approach on the secondary data compiled from the Maharashtra Pollution Control Board (MPCB). The corresponding structural shifting points are identified through the CUSUM of squares (CUSUMQ) test. The empirical results disclose that Kyoto Protocol and lockdown have positively influenced the air quality. This study ends with suitable policy prescriptions.

Environmental degradation is a global concern that results from massive economic activities. Carbon dioxide (CO₂) emissions are one of the environmental degradation indicators. This study investigates the impact of population, oil consumption, international tourist arrival, and corruption on CO₂ emissions in ASEAN’s five developing countries of Malaysia, Indonesia, Thailand, Philippines, and Vietnam from 1998 to 2017. This study employed panel Fixed-effect (FE) regression to estimate the panel data generated by British Petroleum and World Bank. The result revealed that the population has a significant positive effect on CO₂ emissions. Furthermore, oil consumption has a significant positive effect on CO₂ emissions. Meanwhile, the effect of tourism and the corruption perception index (CPI) as a proxy of corruption on CO₂ emissions was positive but not significant. Authorities should construct such policies to reduce CO₂ emissions by applying low-carbon technologies, green mass transport, and creating less corrupt behavior.

The unorganised manufacturing sector contributes one third share of overall manufacturing employment and one fifth share of gross value added of the manufacturing sector. Despite its important role in large-scale employment generation, this sector is neglected by the researchers as well as by the policy makers as compared to the focus given on the organised manufacturing sector. The issues of energy intensity, environment emissions and growth of unorganised manufacturing enterprises (UMEs) remain unexplored. The present chapter attempts to estimate the CO₂ emission and emission intensity (EI) across UMEs on the basis of NSSO Unit Level data of 62nd, 67th and 73rd rounds. It also analyses the growth of UMEs in relation to CO₂ emission and EI. The nature of the sector is very much dispersed. Our study reveals that a portion of unorganised enterprises did not use any energy in their production activities and used manually operated instruments like – handlooms, weaving machines, hand-operated oil and rice mills, etc. The main energy inputs of UMEs are electricity and fuel & lubricants. The CO₂ emission is relatively less in UMEs compared to organised manufacturing enterprises. Across the unorganised manufacturing industries, the higher CO₂ emission are observed in manufacturing of food product industry and other non-metallic mineral industry. The study found that CO₂ EI of UMEs depends on firm-level characteristics like perennial nature, establishment type, urban location and expanding growth status. However, capital intensive UMEs are more polluting.