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Energy-efficiency leads to productivity gains as it can lower operating and maintenance costs, increase production yields per unit of manufacturing input and improve staff accountability. Implementation of energy-efficient technologies amongst industries, the factors influencing them and the barriers to their adoption have been the subject of several studies during the past three to four decades. Though energy-use behaviours of individuals or households are sufficiently explored, industrial energy conservation behaviour is scarcely studied. This study identifies the relationship between the different behavioural elements to open up a door for behaviourally informed intervention research.

Total interpretive structural modelling technique was used to determine the relationship between different elements of the behaviour of energy managers. Expert responses were collected to understand the relationship between the behavioural elements, through telephone interviews.

The study identified the relationship between the behavioural elements and found imperfect evaluation as the key element with the highest driving power to influence other elements.

The authors postulate that a behaviourally informed intervention strategy that looks into the elements with high driving power such as imperfect evaluation, lack of focus on energy-saving measures and the lack of sharing energy-saving objectives can lead to: an increase in the adoption of energy efficiency measures and thereby a reduction in the energy efficiency gap; greater productivity gains and reduced greenhouse gas (GHG) emissions; Preparation of M&V protocol that incorporates behavioural, organisational and informational barriers.

Various policy level interventions and regulatory measures in the energy field which did not address the behavioural barriers are found unsuccessful in narrowing the energy-efficiency gap, reducing the GHG gas emissions and global warming. Understanding the key driving factor of behaviour can help to design an effective intervention strategy to address the barriers to energy efficiency improvement.

Understanding the key driving factor of behaviour can help to design an effective intervention strategy to address the barriers to energy efficiency improvement. This study argues that through the systematic analysis of the imperfect evaluation of energy audit recommendations, it is possible to increase the adoption of energy efficiency measures that can lead to greater productivity gains and reduced GHG emissions.

This study aims at understanding how higher education institutions (HEIs) can contribute to sustainable development, by designing their programmes for bringing about a transformative impact on communities and students, and also to examine what alternative pedagogical approaches could be used for that. In the past decades, HEIs have increasingly created social innovation (SI) programmes, as a way to achieve United Nations Sustainable Development Goals. These community-oriented and field-based programmes are difficult to ally with conventional classroom education. This study explores how these programmes could integrate the participatory approach and what would be the benefits. It also investigates the effectiveness of the experiential learning approach for teaching sustainability.

A case study method is used to document SI projects initiated by an HEI programme in rural India.

It was found that the participatory approach contributes to empowering communities and also benefits the students in terms of academic, professional and personal growth. Empirical findings show that experiential learning is an efficient method to teach sustainability. Ultimately, both pedagogical approaches are found to be mutually beneficial.

This study fills a gap in the literature, by providing empirical evidence on how HEI can implement innovative educational strategies such as participatory approach and experiential learning in their programmes towards teaching sustainability. A conceptual model for HEI interested in developing similar programmes is also proposed. To the best of the authors’ knowledge, this study is one of the first studies focusing on the context of Indian HEI.

In the realm of energy behaviour studies, very little research has been done to understand industrial energy behaviour (IEB) that influences the willingness to adopt (WTA) energy-efficient measures. Most of the studies on energy behaviour were focused on the residential and commercial sectors where the behaviour under investigation was under volitional control, that is, where people believe that they can execute the behaviour whenever they are willing to do so. The purpose of this paper is to examine the factors influencing the industry’s intentions and behaviour that leads to enhanced adoption of energy efficiency measures recommended through energy audits. In particular, this paper aims to extend the existing behaviour intention models using the total interpretive structural modelling (TISM) method and expert feedback to develop an IEB model

TISM technique was used to determine the relationship between different elements of the behaviour. Responses were collected from experts in the field of energy efficiency to understand the relationship between identified factors, their driving power and dependency.

The results show that values, socialisation and leadership of individuals are the key driving factors in deciding the individual energy behaviour. WTA energy-saving measures recommended by an energy auditor are found to be highly dependent on the organisational policies such as energy policy, delegation of power to energy manager and life cycle cost evaluation in purchase policy.

This study has a few limitations that warrant consideration in future research. First, the data came from a small sample of energy experts based on a convenience sample of Indian experts. This limits the generalizability of the results. Individual and organizational behaviour analysed in this study looked into a few select characteristics, derived from the literature review and expert feedback, which may pose questions about the standard for behaviours in different industries.

Reasons for non-adoption of energy audit recommendations are rarely shared by the industries and the analysis of individual and organisational behaviour through structured questionnaire and surveys have serious limitations. Under this circumstance, collecting expert feedback and using the TISM method to build an IEB model can help to build strategies to enhance the adoption of energy-efficient measures.

Various policy level interventions and regulatory measures in the energy field, adopted across the globe, are found unsuccessful in narrowing the energy-efficiency gap, reducing the greenhouse gas (GHG) emissions and global warming. Understanding the key driving factors can help develop effective intervention strategies to improve energy efficiency and reduce GHG emissions.

The industry energy behaviour model with driving, linking and dependent factors and factor hierarchy is a novel contribution to the theory of organisational behaviour. The model takes into consideration both the individual and organisational factors where the decision-making is not strictly under volitional control. Understanding the key driving factor of behaviour can help design an effective intervention strategy that addresses the barriers to energy efficiency improvement. The results imply that it is important to carry out post energy audit studies to understand the implementation rate of recommendations and also the individual and organisational factors that influence the WTA energy-saving measures.

To describe the Pragathi Bandhu Groups (PBG) Model and portray the performance of PBG farmers encouraged by their financial and decision-making participation in micro financing and labor sharing, as well as to analyze the factors that influenced participation of small farmers in PBG.

The empirical study is confined to the small farmers and laborers of PBG functioning in the coastal districts of Karnataka State in India. The study is conducted in Belthangady and Bantwal Taluks of Dakshina Kannada (DK) Districts-Udupi taluk of Udupi District in the State of Karnataka. Primary data from 100 farmer members, selected at random in each of the Taluks, is collected through personal interview by administering semi-structured interview schedules and open discussion. In addition, the data on the functions and the performance of PBG in the State of Karnataka in India are also collected from the official records of Shri Kshetra Dharmasthala Rural Development Project (SKDRDP) and their field-level functionaries through informal discussions. Factor analysis is performed with principal component analysis followed by Varimax rotation to analyze the factors that influenced participation of small farmers in PBG.

Results show that the implementation of PBG Model, through the collective participation of small farmers in micro financing, free labor sharing, financial and decision-making activities underlying the functions of PBG Model, has helped them to achieve robust performance in terms of increased savings mobilization, loan utilization, and value of free labor sharing and acres of land brought under cultivation with the help of irrigation facilities created by them. The factor analysis has derived four factors that influenced the participation of farmers in PBG (agriculture development, financial participation, capacity building, and other benefits) which explain 63.701 of total factor variance.

The findings of this paper can benefit the small farmers and laborers in replicating the PBG Model and its initiatives that address shortages of labor and credit, as well as the high cost of labor, particularly in the unorganized sector in the agrarian economy.

The insights offered are likely to be beneficial to the distressed small farmers, development agencies, and agriculture policy makers to solve the agrarian crisis caused due to shortages of labor and farm credit.

Asset liability management is a multi-dimensional set of activities. Against this backdrop, the purpose of this paper is to build a goal programming model for optimally determining the asset allocation and liability composition for Indian Banks.

The conceptual model framework has been developed and then tested for four banks that typically represent the Indian banking sector. Published balance sheet data were used for the model that span over 1995-2009. The veracity of the model has been tested in terms of its ability to project the optimum asset allocation and liability composition for the year 2010.

The model has been able to generate the optimum asset and liability mix that meets the goals set on the key drivers. The solution provided is realistic and compatible with the actual figures. Sensitivity analysis including current and savings account and interest rate changes has been successfully performed to study impact they cause on profitability.

The model provides an overall approach to asset allocation and liability composition based on past data reflecting the preferences and priorities of the banks with regard to their outlook on setting targets. This may change. The variables like return and risk are stochastic in nature.

The model demonstrated in this paper would be useful to the policy makers in any bank for decision support and planning in view of its ability to incorporate a large number of constraints. Changes in profit could be instantaneously captured through sensitivity analysis.

The goal programming model used here is invariant to the type of bank and year of consideration.

Reducing income gap and enhancing welfare of people can be achieved through improved performance regarding socio-economic indicators, which can support sustainable development. People living in villages tend to migrate to the cities with the hope of enhancing their income. People living in cities and income gap among the people in the cities are expected to increase further. Enhanced living conditions in villages can reduce the need for this migration and increase welfare of the people in the villages. This chapter aims to examine drivers for sustainable smart villages and ways for enhancing and supporting their effectiveness in socio-economic development, in enhancing welfare and living conditions of people living in villages, and in reducing income gap between urban and rural people. This chapter investigates potential and roles of sustainable and smart villages in enhancing welfare and living conditions of people living in villages. Furthermore, this chapter emphasises the villages’ roles in sustainable development as well as importance of transformation of villages into the sustainable and smart ones and establishment of sustainable and smart villages so that convergence, social inclusion and socio-economic indicators can be supported. This chapter explains drivers for transformation of the villages into the sustainable and smart ones as well as establishment of new sustainable and smart villages. This chapter provides recommendations for sustainable and smart villages effective in contributing to sustainable and socio-economic development. This chapter can be useful to urban planners, construction industry stakeholders, policy makers and researchers.

Allocating budget optimally to marketing channels is an increasingly difficult venture. This difficulty is compounded by an increase in the number of marketing channels, a rise in siloed data between marketing technologies, and a decrease in individually identifiable data due to legislated privacy policies. The authors explore the rich attribution modeling literature and discuss the different model types and approaches previously used by practitioners and researchers. They also investigate the changing landscape of marketing attribution, discuss the advantages and disadvantages of different data handling approaches (i.e., aggregate vs. individualistic data), and present a research agenda for future attribution research.

The purpose of this study is to investigate the determinants of consumers' intention to adopt or continue to use Internet-only banks based on the benefit–risk framework and network externality theory. It also examines the difference in the determinants between pre- and postadoption stages of innovation.

The proposed research model was tested by using online survey data collected from a South Korean sample, which was divided into two subgroups of 321 nonadopters and 351 existing users.

In both pre- and postadoption stages, the number of services provided and trust had a significant positive impact on consumers' behavioral intentions, while security risks had a negative impact. Critical mass in the preadoption stage and convenience and economic efficiency in the postadoption stage had positive effects on consumer's adoption intention and continuance intention, respectively.

Internet-only banks must reduce the security risks for consumers and increase their trust. In addition, to facilitate the adoption of nonadopters, focus should be on securing a critical mass; on the other hand, to promote the continued use of existing users, the focus should be on enhancing benefits such as convenience and economic efficiency.

The results of this study confirm the influence of network externalities on consumers' adoption and use of financial technology services and show differences in consumer decision-making according to the innovation diffusion process.

This paper aims to investigate price responses and volatility spillovers between commodity spot and futures markets. The study ultimately seeks the evidence-based claims on the efficiency of the long run and short run horizontal price transmissions from futures markets to spot markets.

This study used the most recent daily price series of pepper, cardamom and rubber, during the period 2004–2019, use “cointegration-ECM-GARCH framework” and verify the persisting validity of the “expectancy theory” of commodity futures pricing.

The results offer overwhelming evidence of futures market dominance in the price discoveries and volatility spillovers in spot markets. However, this paper finds asymmetric responses between cash and futures prices across markets. The hedging efficiency of futures contracts is commodities specific’ where spices futures are more efficient than the rubber futures.

The study passes on vital information to the producers and traders of spices and rubber who have a potential interest in the use of futures contracts to make profits from arbitrage between futures and cash markets.

The paper is unique in terms of understanding asymmetric price linkages in markets for plantation crops.

Agri-biotech multinational enterprises (MNEs) are persisting to push genetically modified plant varieties (GMV) worldwide including emerging countries as a technological solution for sustainable development. However, in emerging countries, the structure and effectiveness of regulation and compliance measures to ensure human and environmental safety are much less developed. There are three types of concerns: the economic risks faced by farmers while using existing low-yielding conventional seed varieties, in the face of inadequate institutional mechanisms and safety nets, the long-term environmental risks, and finally, risks posed by other possible externalities. In an attempt to provide some insight on the aforementioned debate, this chapter focuses on a commercially successful GMV—namely genetically modified cotton, also referred to as Bt cotton. The literature on adoption of Bt cotton is first examined, and its findings are confronted with the reality of the introduction and diffusion of Bt cotton in India to derive inferences on how MNE and emerging countries’ governments can manage coexistence. Our findings indicate that in order to be successful, MNEs have to establish the sociopolitical legitimacy of GMV through investment in outreach with regulatory authorities, government departments dealing with the environmental and bio safety, farmer groups, and nongovernmental organizations (NGOs). MNEs also have to keep in mind that pricing and high technology fee can become an impediment for the legitimization of technology. Finally, MNEs can partner with NGOs to educate and accompany farmers to maximize their livelihood, while preserving the ecological sustainability of their farm lands.