Sanjeev Gupta and Sachin Kashyap
The paper aims to analyse the extent of volatility and generating forecasts of exchange rates of British pound and Indian rupees in US terms.
Abstract
Purpose
The paper aims to analyse the extent of volatility and generating forecasts of exchange rates of British pound and Indian rupees in US terms.
Design/methodology/approach
This study applies different combinations of GARCH and EGARCH models suggested in the Econometric literature to capture the extent of volatility. The forecast of exchange rates of British Pound and Indian Rupees in US terms are generated applying artificial neural network (ANN) technique using different combination of networks with hyperbolic tangent function at hidden and output stage of the model.
Findings
The presence of volatility depicts that there is noise and chaos in the forex market. Prediction of exchange rate of the respective currencies underscores that exchange rates will increase marginally in near future.
Practical Implications
The results proposed in this study will be benchmark for the hedgers, investors, bankers, practitioners and economists to foresee the exchange rate in the presence of volatility and design policies accordingly.
Originality/value
In literature, no study has applied ANN for forecasting exchange rate after measuring the extent of volatility. The present study is a unique contribution in the existing pool of literature to forecasts the concerned variable(s) after ascertaining the noise and chaos in the data by applying GARCH family models.
Details
Keywords
Sachin Kashyap, Sanjeev Gupta and Tarun Chugh
The present work has proposed and employed an innovative hybrid method based on the combination of factor analysis and an artificial neural network (ANN) model to forecast…
Abstract
Purpose
The present work has proposed and employed an innovative hybrid method based on the combination of factor analysis and an artificial neural network (ANN) model to forecast customer satisfaction from the identified dimensions of service quality in India, a developing country.
Design/methodology/approach
The qualitative study is conducted with Internet banking users to understand e-banking clients' perceptions. The data is collected with the help of a questionnaire from randomly selected 208 customers in India. Firstly, factor analysis was performed to determine the influential factors of customer satisfaction, and four factors i.e. efficiency, reliability, security and privacy, and issue and problem handling were extracted accordingly. The neural network model is then applied to the factor scores to validate the key elements. Lastly, the comparative analysis of the actual ANN and the regression predicted result is done.
Findings
The success ability of the linear regression model is challenged when approximated to nonlinear problems such as customer satisfaction. It is concluded that the ANN model is a better fit than the linear regression model, and it can recognise the complex connections between the exogenous and endogenous variables. The results also show that reliability, security and privacy are the most influencing factors; however, problem handling and efficiency have the slightest effect on bank client satisfaction.
Research limitations/implications
This research is conducted in India, and the sample is chosen from the urban area. The limitation of the purposeful sampling technique and the cross-sectional nature of the data may hamper the generalisation of the results.
Originality/value
The conclusions from the study will be helpful for policymakers, bankers and academicians. To our knowledge, few studies used ANN modelling to predict customer satisfaction in the service sector
Details
Keywords
Astha Sanjeev Gupta and Jaydeep Mukherjee
Consumers can spend their disposable income on hedonic consumption or save for the future. Their preferences were altered by the prolonged life and livelihood-threatening…
Abstract
Purpose
Consumers can spend their disposable income on hedonic consumption or save for the future. Their preferences were altered by the prolonged life and livelihood-threatening experiences of the pandemic. This paper aims to study the spillover effect of the pandemic experience on consumer savings attitudes and hedonic purchase preferences in the new normal.
Design/methodology/approach
The authors conducted 35 in-depth interviews with consumers in India. The data were analysed thematically.
Findings
The results showed that when fear of life and negative emotions of the pandemic persisted, consumers became short-term focused, moved towards materialism and increased hedonic spending. Alternatively, individuals who faced substantial financial hardships resorted to an increased preference for savings. The relationship between changes in savings orientation and hedonic consumption was found to be moderated by consumer's individual differences in financial vulnerability and life history strategies.
Practical implications
As the trend towards increased hedonic consumption and preference for luxury products continues, the study findings can be used to devise effective marketing strategies to tap the emerging segment of mass luxury consumption.
Originality/value
Despite ample work being conducted in the hedonic consumption domain, it has not been studied in conjunction with savings orientation, a significant determinant. This research links personal savings orientation with hedonic spending and substantiates that purchase decisions are cognitively weighted as a choice of discretionary spending against the opportunity to save.
Details
Keywords
Astha Sanjeev Gupta, Jaydeep Mukherjee and Ruchi Garg
COVID-19 disrupted the lives of consumers across the globe, and the retail sector has been one of the hardest hits. The impact of COVID-19 on consumers' retail choice behaviour…
Abstract
Purpose
COVID-19 disrupted the lives of consumers across the globe, and the retail sector has been one of the hardest hits. The impact of COVID-19 on consumers' retail choice behaviour and retailers' responses has been studied in detail through multiple lenses. Now that the effect of COVID-19 is abating, there is a need to consolidate the learnings during the lifecycle of COVID-19 and set the agenda for research post-COVID-19.
Design/methodology/approach
Scopus database was searched to cull out academic papers published between March 2020 and June 6, 2022, using keywords; shopping behaviour, retailing, consumer behaviour, and retail channel choice along with COVID-19 (171 journals, 357 articles). Bibliometric analysis followed by selective content analysis was conducted.
Findings
COVID-19 was a black swan event that impacted consumers' psychology, leading to reversible and irreversible changes in retail consumer behaviour worldwide. Research on changes in consumer behaviour and consumption patterns has been mapped to the different stages of the COVID-19 lifecycle. Relevant research questions and potential theoretical lenses have been proposed for further studies.
Originality/value
This paper collates, classifies and organizes the extant research in retail from the onset of the COVID-19 pandemic. It identifies three retail consumption themes: short-term, long-term reversible and long-term irreversible changes. Research agenda related to the retailer and consumer behaviour is identified; for each of the three categories, facilitating the extraction of pertinent research questions for post-COVID-19 studies.
Details
Keywords
Poonam Sharma, Sanjeev Gupta, Ranjan Aneja and Shradha Attri
The present paper aims to conduct a comprehensive scientific mapping of exchange rate forecasting, highlighting trends, developments, and methodological changes. This will provide…
Abstract
Purpose
The present paper aims to conduct a comprehensive scientific mapping of exchange rate forecasting, highlighting trends, developments, and methodological changes. This will provide research scholars, researchers, and policymakers valuable insights to facilitate predictions.
Design/methodology/approach
The researchers performed a bibliometric analysis of exchange rate forecasting using a scientific search method on the Scopus database from 1991 to 2022. They applied a web interface program called Biblioshiny, part of the Bibliometric package built in R by Aria and Cuccurullo (2017). VOSviewer was used to identify the most influential journals, authors, countries, articles, citations, and co-citations from 1,602 documents.
Findings
The conceptual and intellectual framework of the papers under review provided an in-depth and comprehensive analysis of the domain. The research outcomes provided essential information on the subject matter, highlighting the need for further investigation. The study’s findings demonstrate the evolution of the theory of forecasting exchange rates reflecting continuous developments in the methodologies applied to forecast the exchange rates.
Research limitations/implications
The scientific mapping of the present study’s bibliometric analysis is limited to the Scopus database because of its comprehensive coverage of high-quality journals and predefined structures compatible with Bibliometrix software.
Practical implications
The study provides considerable insight into forecasting exchange rates and their interlinkages. By outlining the social and intellectual structure of the field, it directs upcoming scholars about the relevant topics, contexts and potential collaborations emerging in this field. The study also reveals the critical concerns in the area and leads to potential research opportunities.
Social implications
The study sheds light on emerging trends and approaches to forecasting exchange rates and will provide valuable information and insights to policymakers, economists, investors and decision-makers in the financial sector. It will contribute to prioritising research in overlooked areas and support the formulation of effective policies.
Originality/value
This study contributes significantly by bringing together disparate literature on exchange rate forecasting, highlighting important journals, authors and documents, and examining the recent studies on the foreign exchange rate.
Details
Keywords
Sandeep Kumar Gupta, Sanjeev Gupta and S. Gayathiri
The purpose of this paper is to demonstrate the difference in firm performance between pollution prevention and pollution control strategies using a selected case study from the…
Abstract
Purpose
The purpose of this paper is to demonstrate the difference in firm performance between pollution prevention and pollution control strategies using a selected case study from the Indian leather industry.
Design/methodology/approach
This study followed a case study-based inductive research approach to validate the proposed preposition on field. The case-study analysis was based on qualitative and quantitative data. The authors developed a questionnaire and an interview protocol to capture the data about different industrial practices and motivation behind them. The study followed the concept of the triple bottom line approach for assessing the progress of the case firm on sustainability scale.
Findings
With the help of pollution preventive measures, such as replacement of salted skin with fresh skin and chromium salt with a phosphonium-based tanning agent, the case firm could overcome the biggest challenge of bringing down the level of total dissolved solid from 40,000 to 5,000 ppm in the raw effluent. Moreover, the firm has successfully recycled and converted tannery scraps and other waste into organic manure for internal use in its own plantations.
Research limitations/implications
The findings of this study could not be generalized as these are based on a single case study.
Originality/value
This study presents an example of sustainable practices and their benefits to the Indian leather industry to follow.
Details
Keywords
Astha Sanjeev Gupta and Jaydeep Mukherjee
E-retailers face challenges in adding, engaging and retaining customers. Voice interface is a new and more inclusive modality that provides customers with a hands-free, convenient…
Abstract
Purpose
E-retailers face challenges in adding, engaging and retaining customers. Voice interface is a new and more inclusive modality that provides customers with a hands-free, convenient e-shopping option and is relevant for e-retailers. However, the voice interface is significantly different from the text interface that consumers are accustomed to. This study investigates customer experiences with voice interface for search and selection of products on e-commerce platforms and its subsequent impact on customer engagement and enhanced usage.
Design/methodology/approach
We conducted 34 in-depth interviews with executive management students. For analysis and findings, we used a grounded theory paradigm and thematic analysis.
Findings
Based on in-depth probing and analysis consumers' experiences with voice interfaces in e-commerce platforms, we identified two enablers: customer satisfaction and awe-experience that positively impacted and two inhibitors: risk perceptions and inertia that negatively impacted customer engagement and enhanced usage of voice interface.
Originality/value
Voice interface is transforming the customer journey in the online shopping domain. How customers experience voice interfaces when searching and selecting products on e-commerce platforms impacts their engagement with the platform and their intentions to use voice modality to interact with the e-retailer in the future. The findings substantiate tenets of dual-process theory and found that enabling and inhibiting factors are independent and can coexist. The study identifies the most salient factors that positively and negatively affect customer engagement and enhanced usage of voice interfaces.
Details
Keywords
Astha Sanjeev Gupta and Jaydeep Mukherjee
Generative artificial intelligence (GAI) can disrupt how consumers search for information on retail products/services online by reducing information overload. However, the risk…
Abstract
Purpose
Generative artificial intelligence (GAI) can disrupt how consumers search for information on retail products/services online by reducing information overload. However, the risk associated with GAI is high, and its widespread adoption for product/service information search purposes is uncertain. This study examined psychological drivers that impact consumer adoption of GAI platforms for retail information search.
Design/methodology/approach
We conducted 31 in-depth, semi-structured interviews with the lead GAI users regarding product/service information search. The data were analysed using a grounded theory paradigm and thematic analysis.
Findings
Results show that consumers experience uncertainty about GAI’s functioning. Their trust in GAI impacts the adoption and usage of this technology for information search. GAI provides unique settings to investigate potential additional factors, leveraging UTAUT as a theoretical basis. This study identified three overarching themes – technology characteristics, technology readiness and information characteristics – as possible drivers of adoption.
Originality/value
Consumers seek exhaustive and reliable information for purchase decisions. Due to the abundance of online information, they experience information overload. GAI platforms reduce information overload by providing synthesized and customized product/service search results. However, its reliability, trustworthiness and accuracy have been questioned. The functioning of GAI is opaque; the popular technology adoption model such as UTAUT is general and is unlikely to explain in totality the adoption and usage of GAI. Hence, this research provides the adoption drivers for this unique technology context. It identifies the determinants/antecedents of relevant UTAUT variables and develops an integrated conceptual model explaining GAI adoption for retail information search.
Details
Keywords
Astha Sanjeev Gupta and Jaydeep Mukherjee
COVID-19 pandemic-related Government restrictions on the movement of people resulted in consumers moving away from retail outlets. However, sporadic instances of an unexpected…
Abstract
Purpose
COVID-19 pandemic-related Government restrictions on the movement of people resulted in consumers moving away from retail outlets. However, sporadic instances of an unexpected surge in retail buying happened across the world immediately after the lifting of such restrictions. This uncommon phenomenon, termed revenge buying, offered an opportunity to revive retail businesses. This paper applies Reactance Theory (RCT) and Self-determination Theory (SDT) to model consumers' revenge buying intentions.
Design/methodology/approach
Data was collected from 384 respondents in India using validated scales. The study used structural equation modelling for model testing.
Findings
COVID-19 restrictions resulted in autonomy need frustration in consumers, which induced psychological reactance and perceived stress. Psychological reactance positively impacted, while perceived stress negatively impacted revenge buying intentions. Thus, revenge buying was observed only when the psychological reactance was more than perceived stress.
Research limitations/implications
This study, conducted in only one country with a limited convenience sample, limits the generalizability of findings.
Originality/value
This research model the psychological consequences of need frustration to explain the sporadic incidences of revenge buying in retail outlets. Further, it proposes sales recovery strategies for retailers in the immediate post-pandemic market scenarios. Retailers' strategies should focus on alleviating stress and anxiety because of health concerns, highlighting the retail buying experience to stimulate the need to visit the outlet and positioning retail buying as a potential reactance response by consumers.
Details
Keywords
Astha Sanjeev Gupta and Jaydeep Mukherjee
Short-term changes in consumers' shopping behaviour due to the Covid-19 pandemic have been studied, but not the long-term effects. This study fills this gap by exploring the…
Abstract
Purpose
Short-term changes in consumers' shopping behaviour due to the Covid-19 pandemic have been studied, but not the long-term effects. This study fills this gap by exploring the long-term changes in consumers' retail shopping behaviour, due to their experiences of the Covid-19 pandemic.
Design/methodology/approach
Qualitative data were collected from one hundred fifty-nine respondents, and grounded theory approach was applied for interpretation. Gioia thematic analysis method, open coding, and axial coding were used for analysis.
Findings
Individuals who positively approached their experiences during the Covid-19 demonstrated increased pro-sustainable and pro-environmental self-identity, resulting in sustainable consumption and a shift to online shopping. Individuals having overpowering negative experiences demonstrated heightened fear of missing out (FOMO), loss aversion, and rumination. While shopping, they demonstrated herd behaviour and shifted to online shopping.
Research limitations/implications
This study highlights emotional and psychological mechanisms influencing long-term changes in consumer shopping preferences post Covid-19 pandemic. The generalizability of the findings is limited due to the study's exploratory nature and the sample size.
Originality/value
This study contributes to shopping behaviour literature by uncovering novel constructs of self-identity, loss aversion, FOMO, and rumination as antecedents to long-term shopping behaviour changes post-Covid-19. It provides a new conceptual model of consumers' shopping behaviour, which may be empirically validated.