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The purpose of this paper is to explore the composition of “tourism experience” of tourist visiting during the Nabakalebara event at Puri, India.

The paper applies data reduction using exploratory factor analysis on a sample of 300 respondents drawn during the event and condenses a set of 20 attributes into a list of five compressible factors.

The research shows that visitors visualise tourism experience as a combination of five factors: education, entertainment, esthetics, escapism and ease of facilities. They assigned different weightage in terms of significance to each of these factors. Internal configuration of these factors also reveals interesting patterns.

A non-probability sampling method is applied in this research. Future studies should replicate the research in different social, economic and geographical context to see if the factor composition and structure remain unchanged.

Organisers should focus on improving ease of facilities. Disproportionate expenditure on adding to other factors is not expected to yield matching dividends.

The study assumes significance as this kind of event used to happen on every 15 years. This attracts millions of visitors. The paper explores the expectation of visitors.

This paper is among the few works done on understanding tourism experience during the Nabakalebara at Puri, India. It adds significantly to the meagre body of knowledge in the area of tourism experience.

The paper has proposed to implement gray wolf optimization (GWO)-based filter-type proportional derivative with (FPD) plus (1+ proportional integral) multistage controller in a three-area integrated source-type interlinked power network for achieving automatic generation control.

For analysis, a three area interconnected power system of which each area comprises three different generating units where thermal and hydro system as common. Micro sources like wind generator, diesel generator and gas unit are integrated with area1, area2 and area3 respectively. For realization of system nonlinearity some physical constraints like generation rate constraint, governor dead band and boiler dynamics are effected in the system.

The supremacy of multistage controller structure over simple proportional integral (PI), proportional integral, derivative (PID) and GWO technique over genetic algorithm, differential evolution techniques has been demonstrated. A comparison is made on performances of different controllers and sensitivity analysis on settling times, overshoots and undershoots of different dynamic responses of system as well as integral based error criteria subsequent a step load perturbation (SLP). Finally, sensitive analysis has been analyzed by varying size of SLP and network parameters in range ±50 per cent from its nominal value.

Design and implementation of a robust FPD plus (1 + PI) controller for AGC of nonlinear power system. The gains of the proposed controller are optimized by the application of GWO algorithm. An investigation has been done on the dynamic performances of the suggested system by conducting a comparative analysis with conventional PID controller tuned by various optimization techniques to verify its supremacy. Establishment of the robustness and sensitiveness of the controller by varying the size and position of the SLP, varying the loading of the system randomly and varying the time constants of the system.

Launching a new product successfully in a multi-brand portfolio is one of the major challenges a pharmaceutical marketer faces. This study aims to examine the role of detailing of new brands on physicians’ prescription behaviour as compared to established brands. Further, the study explores mediating role of detailing priority and detailing time on the relationship between detailing of new versus established brands and physician’s prescription behaviour.

This study was conducted as a real-world observational study involving field research. In total, 338 physicians, 90 PSRs and 44 field managers participated in this study. A serial mediation model (Hayes, Model 6) was used to examine the relationship. Regression analysis with bootstrapping was used to test the hypotheses.

Detailing of new versus established brands has a differential effect on physicians’ prescription behaviour. In addition, this relationship is serially mediated by detailing priority and detailing time.

Results suggest that detailing priority and detailing time positively and significantly alter the relationship between the detailing of new brands and physicians’ prescription behaviour as compared to established brands. While, in the absence of mediators, established brands generate higher prescriptions than new brands, the serial mediating effect helps new brands to generate more prescriptions as compared to established brands.

This research highlights the importance of detailing priority and detailing time for the successful launch of the new products. It presents compelling evidence for practicing managers to effectively use a “predetermined detailing plan” vis-à-vis “individualized detailing strategy” during the launch of a new brand.

To the best of the authors’ knowledge, this is the first study to evaluate the role of detailing priority and detailing time as mediators between the relationship of detailing and physicians’ prescription behaviour. This is also one of the rare studies to use real-world observational study methodology for conducting research.

This study aims to extend existing theories and fills research gaps regarding the acceptance and use of new technologies by consumers by exploring the adoption of app-cab services in India. Through the application and comparison of a unified theory of acceptance and use of technology (UTAUT) and UTAUT 2/expanded-UTAUT (E-UTAUT) models, this paper empirically tests the relationships between important constructs related to technology adoption, acceptance and utilization in India’s emerging economy.

In total, 612 responses to a questionnaire of active and regular users of app-cab services in India are examined. Path analysis and structural equation modeling presents interesting findings indicating that the expanded models have huge implications for the Indian app-cab industry.

This paper finds that the UTAUT 2/E-UTAUT models are a good fit for consumers and their behavior toward technology-based services. In particular, this study, one of the first of its kind, examines consumer acceptance and use behavior and identifies the factors that influence customer behavior with regard to new technology (app-cab services) in an emerging economy (India). Theoretical and practical implications are discussed.

Very few studies are available on app-cab adoption in emerging economies.

This study aims to assess young customers’ repurchasing intentions toward green plastic products by incorporating green trust model into green purchase intention model. It also evaluates the role of gender moderation in the green repurchase intention formation model.

A total of 314 young consumers of green plastic products in Bandung, Indonesia were determined for this study. This study used variance-based partial least squares (PLS) to evaluate the proposed model and examine the hypothesized relationship, by means of SmartPLS 3. The construct validity and reliability were evaluated by testing the measurement model, while the proposed hypotheses were examined by testing the structural model.

The assessment of the proposed model using PLS reveals that the incorporation of green trust model increases the prediction strength of green repurchase intentions model on green plastic products. Further, this study shows that, in general, gender did not moderate the formation of green repurchase intentions.

Besides broadening the green repurchase intention theory, this finding offers a direction for green plastic businesses to improve their capability and their marketing strategies. This study offers an important contribution in understanding young consumers’ intentions to buy green plastic products, although it has several drawbacks. In the future, to increase its generalization, this study can be replicated on young consumers in other developing and developed countries, and this model can also be tested in other segments.

To the best of the authors’ knowledge, there are no published studies that have tested the repurchase intention model for green plastic products, and none of the past studies have incorporated these models to explain repurchase intention toward green plastic products. Furthermore, the inclusion of gender roles in green repurchase intentions for green plastic products is important to be explored.

The purpose of this paper is to study and describe several biases in investment decision-making through the review of research articles in the area of behavioral finance. It also includes some of the analytical and foundational work and how this has progressed over the years to make behavioral finance an established and specific area of study. The study includes behavioral patterns of individual investors, institutional investors and financial advisors.

The research papers are analyzed on the basis of searching the keywords related to behavioral finance on various published journals, conference proceedings, working papers and some other published books. These papers are collected over a period of year’s right from the time when the most introductory paper was published (1979) that contributed this area a basic foundation till the most recent papers (2016). These articles are segregated into biases wise, year-wise, country-wise and author wise. All research tools that have been used by authors related to primary and secondary data have also been included into our table.

A new era of understanding of human emotions, behavior and sentiments has been started which was earlier dominated by the study of financial markets. Moreover, this area is not only attracting the, attention of academicians but also of the various corporates, financial intermediaries and entrepreneurs thus adding to its importance. The study is more inclined toward the study of individual and institutional investors and financial advisors’ investors but the behavior of intermediaries through which some of them invest should be focused upon, narrowing down population into various variables, targeting the expanding economies to reap some unexplained theories. This study has identified 17 different types of biases and also summarized in the form of tables.

The study is based on some of the most recent findings to have a quick overview of the latest work carried out in this area. So far very few extensive review papers have been published to highlight the research work in the area of behavioral finance. This study will be helpful for new researches in this field and to identify the areas where possible work can be done.

Practical implication of the research is that companies, policymakers and issuers of securities can watch out of investors’ interest before issuing securities into the market.

Under the Social Implication, investors can recognize several behavioral biases, take sound investment decisions and can also minimize their risk.

The essence of this paper is the identification of 17 types of biases and the literature related to them. The study is based on both, the literature on investment decisions and the biases in investment decision-making. Such study is less prevalent in the developing country like India. This paper does not only focus on the basic principles of behavioral finance but also explain some emerging concepts and theories of behavioral finance. Thus, the paper generates interest in the readers to find the solutions to minimize the effect of biases in decision-making.

From the last few decades, environmental issues have become a global concern. Consumption activities are given much attention in the marketing literature, whenever the question about protecting the environment arises. The responsibility of the consumer toward the environment is a major concern and the purpose of this study is to prioritize factors responsible for determining environmental responsibility among young consumers. This research will provide valuable insights to the marketers in targeting those particular areas which according to young consumers are highly ranked/prioritized for being environmentally responsible.

In this study, data were collected from 400 young consumers from Punjab and Chandigarh. Fuzzy analytical hierarchy process (F-AHP) was applied to prioritize or rank the factors on the basis of significance for being environmentally responsible. The primary factors considered for further analysis were knowledge and awareness, attitude, green consumer value, emotional affinity toward nature, willingness to act and environment-related past behavior.

Results of the study depicted knowledge and awareness as the highest-ranked and prioritized factor for young consumers to become environmentally responsible, while environment-related past behavior emerged as the least important factor for consumers' environmental responsibility.

Data were collected from the young consumers of Punjab and Chandigarh only and only a few factors of consumers' environmental responsibility were considered for further analysis which depicts the limitation of the study.

The research study is highly useful for the government and the business firms to target the highly prioritized factors of environmental responsibility which will promote green consumption practices and behavior among young consumers.

Previous researches have explored the factors of environmental responsibility and modeled their relationships. However, the present study has employed the multi-criteria decision-making technique to provide valuable insights for marketers, academicians and practitioners about the drivers of consumers' environmental responsibility which adds value to the existing knowledge base.

Over the last few decades, there has been a substantial increase in environmentally conscious consumers' willingness to switch their preferences from mainstream products to green products. Hence, it becomes essential for academicians and marketers to understand the notion, attributes and a comprehensive profile of green consumers. Since consumer attitude towards green products is not widely studied in developing countries, the present study aims at exploring the profile of green consumers in India (Punjab State) based on the same in the Indian context.

The study used the survey method, and a sample of 400 respondents was selected from the Punjab State of India. Initially, principal component analysis was employed to reduce the dimensions. Following this, cluster analysis was applied to segment consumer market in distinctive segments. Results of cluster analysis were validated with discriminant analysis and finally, differences amongst the segments of green and non-green consumers were examined to build on the profile of green consumers.

The study segmented the consumer market based on consumer attitude towards green products. Results of the study revealed four distinct segments. “Dynamic Green”, the largest cluster, presents truly green consumers who exhibit a positive attitude towards green products. Finally, the study highlighted the attitudinal profile of green and non-green consumers and differences amongst the segments were explained.

Similar study should be conducted in other developing/developed countries. Furthermore, cross-cultural studies can be undertaken to contrast consumer attitude towards green products. The study may also be extended to probe the connection between consumers' attitude and actual behaviour towards green products.

The study examined the role of consumer attitude towards green products in identifying the distinct segment of green consumers and determining different configurations of consumer characteristics to build on the profile of green consumers.

This study aims to develop and empirically test a comprehensive framework in which to understand the determinants of guests’ behavior to use green peer-to-peer (P2P) accommodation in the UK P2P context by emerging the theory of planed behavior, environmental commitment theory and the value-belief-norm (VBN) theory into one model.

Adopting a quantitative approach, the present study proposes an integrated model integrating theory of planed behavior, environmental commitment theory and the VBN theory and subsequently tests the model using structural equation modeling data analysis. Data collected from 721 respondents were analyzed through (AMOS) to test the proposed model.

The results indicate that our integrated framework demonstrates a favorable level of prediction power for guests’ behavior, which verified the superiority of the suggested framework. Furthermore, the findings verified the moderating impact of guest attributes on guests decision regarding the booking process.

This study contributes to the existing theory and practice by offering important insights about determinants of guests’ behavior to use green P2P accommodation in the UK P2P context.

This research was the first to explore the determinants of guests’ behavior to use green P2P accommodation in the UK P2P context.

Building on the information processing perspective, the authors propose that both internal and external supply chain risk management (SCRM) practices play essential roles in mediating supply chain disruption orientation (SCDO) to exercise an influence on resilience. The authors also put forward analytics capability as an important moderator in the above-mediated relationship.

The authors collected 170 match-paired questionnaires from Chinese firms to test our model. The authors further interviewed some managers to supplement key quantitative results.

First, SCDO positively affects resilience via internal and external SCRM practices. Second, the mediating effects of internal and external SCRM practices are stronger when analytics capability is higher. Third, analytics capability positively moderates the positive effect of SCDO on SCRM practices. Meanwhile, it does not moderate the positive effect of SCRM practices on resilience.

Our study contributes to SCRM-related and IT-related literature by considering the content, mediating mechanisms (i.e. internal and external SCRM practices) and boundary conditions (i.e. data analytic capability) of SCDO in shaping resilience in the digital supply chain.

Our study helps remind managers that firms build disruption orientation, develop different SCRM practices and leverage analytics capability to improve resilience amid unexpected and unplanned disruptions.

Our study sheds light on the roles of both internal and external SCRM practices. Furthermore, this research helps explain how SCDO motivates resilience through SCRM practices, particularly for those firms that have higher analytics capability.