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This study aims to obtain an understanding of the impact of personal cultural orientation on potential consumers’ intention toward the purchase of high-involvement green products, specifically, electric two-wheelers in India, which is one of the largest emerging markets of the world.

A self-administered questionnaire comprising a total of 30 items was administered over a sample of 582 respondents. The structural equation modeling using partial least square was used to analyze the relative impact of different cultural dimensions on consumers’ green purchase intention. Geert Hofstede’s typology of culture was used to represent personal cultural orientation and four of the five dimensions, namely, collectivism, long-term orientation (LTO), masculinity and uncertainty avoidance were studied.

Findings of the study revealed that collectivism, LTO and masculinity appear to be significant cultural dimensions that influence Indian consumers’ intention to purchase electric two-wheelers. Collectivism is the most influential dimension, followed by LTO and masculinity.

This study helps in expanding literature in the area of green purchase by providing insight on how consumers’ individual cultural orientation influences their purchase of eco-friendly products such as electric two-wheelers.

The findings of the study offer insights, which can be useful for marketers in developing various promotional strategies, as consumers’ cultural values have significant implications for decisions with respect to the advertisement content.

This study illustrates the relative impact of different dimensions of national culture (measured at consumers’ personal level) on consumers’ green purchase intention. Such a study appears to be important in extending current knowledge on green purchase behavior in one of the largest emerging markets such as India.

The purpose of this paper is to examine how the various perceived risk facets such as financial risk, performance risk, psychological risk, social risk, and physical risk influence the Indian consumers’ perceived overall risk during the purchase of green products such as energy-efficient LED light bulbs.

A self-administered questionnaire comprising a total of 29 items was employed over a sample of 272 respondents. The structural equation modeling using partial least squares was used for data analysis.

Psychological risk emerged as the most influential of the various risk facets in affecting perceived overall risk. Financial, physical, and performance risks emerged as the second, third, and fourth most influential risk facets, respectively, which affect the perceived overall risk. Surprisingly, social risk did not emerge as an influential facet when it comes to affecting perceived overall risk. Further, psychological and financial risks appeared to have a positive medium-level influence on the perceived overall risk, whereas physical and performance risks appeared to have a positive weak influence on the perceived overall risks. The influence of financial risk on the perceived overall risk was found to be partially mediated by performance risk.

The study is unique in the sense that it reflects the risk perception of potential consumers in one of the largest emerging markets of the world, when it comes to purchase of green products.

The purpose of this study is to broadly examine the role of marketing–finance interface factors for value creation. Specifically, the study investigates the influence of discretionary expenditures such as advertisement on valuation of brands and firms within the framework of risk factors.

To test the model and hypotheses of this study as it has the possibilities of multiple causations among different variables used in the system. Some independent variables are not truly independent and there is a possibility of biased estimation and inconsistent results. Hence a dynamic simultaneous equation model is used including the instrumental variable approach.

The study provides evidence for direct association between brand value and firm value which is represented by the joint impact of both operating and stock market performance. The results establish the direct relationship between brand and firm value and signify the relevance of intangible value creation.

This study addresses the gap in the research which examines the role of marketing decisions on value creation which jointly impacts both operating and stock market performance.

The purpose of this paper is to deal with profit maximization problem of two-layer supply chain (SC) under fuzzy stochastic demand having finite mean and unknown variance. Buyback policy is employed from the retailer to supplier. The profit of the supplier solely depends on the order size of the retailers. However, the loss of shortage items is related to loss of profit and goodwill dependent. The authors develop the profit function separately for both the retailer and supplier, first, for a decentralized system and, second, joining them, the authors get a centralized system (CS) of decision making, in which one is giving more profit to both of them. The problem is solved analytically first, then the authors fuzzify the model and solve by fuzzy Hausdorff distance method.

The analytical models are formed for both centralized and decentralized systems under non-cooperative and cooperative environment with suitable constraints. A significant assumption on density function, namely Cauchy-type density function, is introduced for demand rate because of its wider range of the retailers’ satisfactions. Fuzzy Hausdorff metric is incorporated within the fuzzy components of the fuzzy sets itself. Using this method, the authors find out closure values of both centralized and decentralized policies, which is an essential part of any cooperative and non-cooperative two-layer SC models. Moreover, the authors take care of the profit values with corresponding ambiguities for both the systems explicitly.

It is found that the centralize policy of SC could only be able to maximize the profit of both the retailers and suppliers. All analytical results are illustrated numerically along with sensitivity analysis and side by side comparative studies between Hausdorff and Euclidean distance measure are done exclusively.

The main focus of attention of the proposed model is given to usefulness of Hausdorff distance. Unlike other distances, Hausdorff distance can take special care on the similarity measures of different fuzzy sets. Researchers have been engaged to use Hausdorff distance on the different fuzzy sets but, in this study, the authors have used it within the components of a same fuzzy set to gain more closure values than other methods.

The use of this Hausdorff distance approach is totally new as per literature survey suggested yet. However, the Cauchy-type density function has not been introduced anywhere in SC management problems by modern researchers still now. In crisp model, the sensitivity on goodwill measures really provides a special attention also.

The purpose of this paper is to provide the maintenance personnel with a methodology for modeling and estimating the reliability of critical machine systems using the historical data of their inter‐failure times.

The failure patterns of five different machine systems were modeled with NHPP‐log linear process and HPP belonging to stochastic point process for predicting their reliability in future time frames. Besides the classical approach, Bayesian approach was also used involving Jeffreys's invariant non‐informative independent priors to derive the posterior densities of the model parameters of NHPP‐LLP and HPP with a view to estimating the reliability of the machine systems in future time intervals.

For at least three machine systems, Bayesian approach gave lower reliability estimates and a larger number of (expected) failures than those obtained by the classical approach. Again, Bayesian estimates of the probability that “ROCOF (rate of occurrence of failures) would exceed its upper threshold limit” in future time frames were uniformly higher for these machine systems than those obtained with the classical approach.

This study indicated that, the Bayesian approach would give more realistic estimates of reliability (in future time frames) of the machine systems, which had dependent inter‐failure times. Such information would be helpful to the maintenance team for deciding on appropriate maintenance strategy.

With the help of Bayesian approach, the posterior densities of the model parameters were found analytically by considering Jeffreys's invariant non‐informative independent prior. The case study would serve to motivate the maintenance teams to model the failure patterns of the repairable systems making use of the historical data on inter‐failure times and estimating their reliability in future time frames.

The study intends to evaluate the impact of inflation expectation on the performance of listed commercial banks in India during 2005–2021. Inflation expectation is considered as a direct policy tool by the policymakers for stability of the economy. The study explores how inflation expectation affects the performance indicators of the Indian banking industry while controlling for a wide range of bank-specific factors.

The study applies the generalized method of moments (GMM) on a panel sample of 27 listed bank to analyse the impact of inflation expectation on banking sector performance. The data on inflation expectation are obtained from the household inflation expectation survey introduced in India by the Reserve Bank of India in 2005. Return on assets (ROA), return on equity (ROE) and Tobin's Q have been considered as the banking performance indicators in this study.

Empirical results exhibit that inflation expectation is instrumental in deciding the banking sector's performance. Inflation expectation has been found to have a significant and positive impact on accounting-based measures of banking performance. At the same time, it shows negative impact on the marketing-based measure.

The study gives a clear picture about how inflation expectation affects the banking performance and the monetary policy of the country. The study provides crucial insights to develop strategic decisions for the Indian banking sector. The adoption of proper macroeconomic policies, taking into account inflation expectation levels, is instrumental in enhancing bank's performance and in achieving economic growth.

This study contributes to the growing body of literature on the impact of inflationary conditions on banking performance. The originality lies in capturing the role of inflation expectation solely in determining banking sector performance.

The aim of this paper is to show how a bank's brand value is quantitatively assessed using the Interbrand methodology, taking into account the specifics of the banking market. Therefore, the objective of this paper is to review the ways in which brands contribute to the higher market value of banks by strengthening intellectual capital (IC), as reflected in increased levels of competitiveness and the reputation that the bank maintains in the minds of customers.

This paper applies the Interbrand methodology, which indicates that the assessment of brand value implies the determination of economic profit as the difference between the net operating profit after tax and the cost of capital. The brand profit is then calculated as the product of the economic profit and the index of the brand role. Brand value is obtained as the product of the brand's profit and the discount rate of the brand. In order to further test the results obtained through the application of the Interbrand methodology, linear regression was applied to the panel data in order to provide more efficient econometric estimates of the model parameters.

This research has shown that the Interbrand methodology's empirical foundations lie in the Montenegrin banking market, but also that, out of all of the analyzed parameters, the greatest significance is obtained from the profit of the brand, which influences the value of bank brands.

This research is related to the service sector–in this case, financial services – meaning that it is necessary to adjust the calculation of the weighted average cost of capital. Although the banking sector is a very competitive market, a limitation exists in the fact that the research was conducted only in Montenegro. In other words, in order to achieve a more detailed analysis, this methodology should be applied to more countries, such as those within the Western Balkans, as they have a relatively similar level of development.

A main contribution of this paper is that the assessment of the banks' brand value could be useful to future investors. Therefore, the improvement of the financial sector–in this case, banks–as institutions that hold a dominant position in the financial market in Montenegro, is a particularly important issue. It is important to point out that the research conducted could serve as a means by which to bridge the gap between theory and practice, since the methodology of the consulting company Interbrand has been optimized and adjusted to the Montenegrin banking market.

On considering the fact that most countries of the Western Balkans are at a similar level of development, the authors can conclude that, with the help of this adapted form of methodology, this research can be applied to assess banks' brand value in neighboring countries.

This paper serves as the basis for further research as the analysis of banking institutions that comprise both marketing and financial aspects, i.e. the application of the Interbrand methodology, was not conducted in Montenegro. Also, this paper overcomes the literal gap between theory and practice as there is little research thus far involving the application of the Interbrand methodology to the field of finance; especially in the field of banking. The authors point out the specifics of the banking sector as a key explanation for this. This is why it is necessary to make certain adjustments to the methodology. The research has positive implications for banks' internal and external stakeholders. The originality of this research is reflected in the fact that the Interbrand methodology has been optimized in order to assess the brand of banks, taking into account the specificity of the analyzed market. Brand is analyzed as a component of IC: another factor that exemplifies the value of this research.