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Research on corporate social responsibility (CSR) activities and consumer perception of CSR activities is increasing over the recent past. The purpose of this paper is to gain an understanding of the consumer perceptions of CSR activities of banks in India. It provides insights on whether consumers want their banks to take up CSR initiatives and would these perceptions influence their attitude towards the bank.

Self-report questionnaires were personally administered by the researchers and their team. Respondents’ responses were based on their awareness of their bank’s involvement in CSR initiatives. The study uses convenience sampling, given the resource limitations. The research was conducted in the city of Nashik, India during June–October 2015.

The results of the study show that consumer perception towards the CSR activities of the bank influenced their attitude and satisfaction. Though consumers expressed a need for their bank’s taking up CSR initiatives, this need did not influence their attitude towards the bank, contradicting studies in the past. Consumer perception of the bank’s involvement in the CSR activities was moderate, indicating that banks need to increase their communication about the CSR initiatives undertaken by them.

Unique contribution of current research is that the CSR reputation and CSR concern of consumers in the Indian context have been investigated for their influence on consumer attitude. Unlike previous studies, CSR concern does not influence consumer attitude or satisfaction. Findings provide important insights for practitioners and academicians focussing on the banking sector in India.

Little research is reported on consumer perception of CSR in banking sector. Current research tries to fill this gap.

The purpose of this paper is to identify factors influencing the financial attitudes of Indian women and then classifying Indian women based on these attitudes. These clusters are then studied for their characteristics.

Literature reviewed led to the identification of variables influencing financial attitude of women. Nine of these variables (anxiety, interest in financial issues, intuitive decisions, precautionary saving, free spending, materialistic and fatalistic attitude, propensity to plan for long and short-term financial goals) were put through confirmatory factor analysis. These factors were then used as a basis for cluster analysis. The study was conducted in the city of Nashik, India, in 2014-2015, using convenience sampling. A self-reported questionnaire was used for the survey.

Results of the study showed that only a third of the respondents did not buy any financial products. The most preferred financial products of Indian women were fixed deposits and insurance policies. Four clusters of women were identified, based on their financial attitudes – judicious consumers, conservative consumers, acquisitive consumers, unsure consumers. An analysis of the dispersion of the clusters shows that interest in financial issues has the greatest influence in the formation of clusters followed by the propensity to plan and materialistic attitude. Fatalistic attitude had the least influence in the formation of clusters.

The current study uses convenience sampling which is non-probability-based sampling and hence, lack generalizability of results. The sample for the current study is small, given the resource availability of the researcher and the unwillingness of women to participate in the survey.

The paper provides important insights for the marketers of financial services, in understanding the women consumers in the expanding Indian market.

An understanding of the women consumers would help marketers develop products and financial literacy programs that suit the requirements of each specific group. By doing so the programs and communcation would be more effective.

This paper discusses the financial attitudes and behavior of Indian women and further clusters these women based on their financial attitudes.

To reduce the electricity consumption in our homes, a first step is to make the user aware of it. Reading a meter once in a month is not enough, instead, it requires real-time meter reading. Smart electricity meter (SEM) is capable of providing a quick and exact meter reading in real-time at regular time intervals. SEM generates a considerable amount of household electricity consumption data in an incremental manner. However, such data has embedded load patterns and hidden information to extract and learn consumer behavior. The extracted load patterns from data clustering should be updated because consumer behaviors may be changed over time. The purpose of this study is to update the new clustering results based on the old data rather than to re-cluster all of the data from scratch.

This paper proposes an incremental clustering with nearness factor (ICNF) algorithm to update load patterns without overall daily load curve clustering.

Extensive experiments are implemented on real-world SEM data of Irish Social Science Data Archive (Ireland) data set. The results are evaluated by both accuracy measures and clustering validity indices, which indicate that proposed method is useful for using the enormous amount of smart meter data to understand customers’ electricity consumption behaviors.

ICNF can provide an efficient response for electricity consumption patterns analysis to end consumers via SEMs.

Studies addressing barriers to implement lean production (LP) from the perspective of risk management (RM) have not been so usual in the literature. Re-interpreting barriers to lean as potential risks that should be avoided or mitigated, this paper aims to identify and categorise risks in the implementation of LP to propose a framework, which provides an overview of risks that negatively influence this process.

Through a systematic literature review exploring papers in the Web of Knowledge database, 69 papers were selected. A descriptive analysis was first carried out to identify the evolution in the number of papers, usual terminologies, research methods, analytic tools and the RM phases approached by each paper. After that, an in-depth study of the paper sample was conducted to find risk factors and categories.

The authors found a list of 61 risk factors. Then, considering the sources of the identified risk factors, six broad categories of risks were defined, namely, top management risks, human resources risks, lean knowledge risks, technical risks, supply chain risks and cultural risks. The authors also defined 34 subcategories, resulting in a risk classification framework.

Based on the review, the authors identified literature gaps and provided a research agenda. A noteworthy research limitation is that the authors only selected papers about LP, so the authors might have missed some potential risks in lean implementation that may arise from other-related areas. Thus, the exploration of lean risks adopting other perspectives may constitute a promising pathway for further research.

The classification framework may help practitioners and researchers in risk identification, evaluation and mitigation. It can also enable the creation of response plans to risks in lean production implementation, as it indicates the potential risks that may be faced along with this process.

This study contributed to add the perspective of RM to the literature on lean implementation. The introduction of RM concepts and tools may generate more robust models of lean implementation. Therefore, the classification framework may represent a starting point to produce new knowledge about this research topic.

The purpose of this paper is to determine the degree of lean awareness and implementation and to identify the perception on tools, enablers, barriers and potential benefits of lean in the Indian coal mining industry.

A systematic review of lean literature and expert opinion was used to design the survey instrument. Data were collected through electronic survey and traditional pencil and paper approach. In order to test the research hypotheses, independent sample t-tests were done.

The study reveals that there is a certain degree of lean awareness although the level of lean implementation is still at a nascent stage in the Indian coal mining sector. The main applicable tools, barriers, enablers and benefits have also been identified based on 54 respondents out of 109 suitable respondents.

In this study, relatively the maximum participants were from the mines located in Eastern India. Thus, a certain level of bias can be anticipated. The findings would help the decision makers, researchers and practitioners to better utilize the available resources for lean implementation and support the existing academic research on lean.

The concept of lean in mining industry is relatively a new paradigm and there is a lack of empirical study that explores applicable tools, barriers, enablers and benefits of lean in Indian mining industry. The study addresses this gap in the lean literature.