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Option pricing theory enables computation of the price of an option using different variables associated with the underlying security and options contract. The purpose of this study is to assess research trends that emerged in the field of option pricing. This study reviews existing literature of the option pricing domain, both qualitatively and quantitatively, and identifies potential themes for future research.

This study adopts bibliometric analysis method to explore literature published in the option pricing domain. As part of bibliometric analysis, this study considers both descriptive and network analysis to assess publication trends. For descriptive analysis, the “bibliometrix” package proposed by Aria and Cuccurullo (2017) is used and for network analysis, VOS viewer (Van Eck and Waltman, 2017) and Gephi (Bastian et al., 2009) are used.

This study identifies research trends, top researchers, articles, journals and contributions from institutions and countries in the option pricing domain. It identifies four clusters that show different directions and also focuses on past studies on the same subject. It explores research gaps by performing an in-depth analysis of existing literature on option pricing and suggests the way forward for research in this area.

To the best of the authors’ knowledge, no previous studies have attempted to analyze the literature published in the option pricing domain. This study fulfils this research gap by conducting a comprehensive analysis of studies in the option pricing area. This study identifies quality research work published in the domain, research trends, contribution by most relevant researchers, contributions across geographies and institutions and the connections among these aspects. This study also identifies important themes and provides directions for future research.

This research aims to examine the impact of friction stir processing (FSP) treatment on an aluminum alloy, especially the AD31T alloy derived from the Al-Fe-Mg-Si system. The aim is to assess the influence of different processing techniques on the microstructure and physical and mechanical characteristics of the material, with a specific focus on structural and bulk imperfections inside the stir zone (SZ).

The study demonstrates that augmenting the linear velocity of the tool within the 25–100 mm/min range results in significant enhancements. The enhancements include a decrease in the heat-affected zone (HAZ), a reduction in the extent of volume defects inside the SZ and a more uniform deformation. The microstructural analysis results are corroborated by data acquired from microhardness and electrical conductivity studies, confirming the beneficial influence of modifying the tool’s linear velocity on the material parameters.

This study provides significant observations on the changes in microstructure and the generation of flaws throughout the process of FSP of AD31T alloy. These results have practical implications for improving the characteristics of the alloy and optimizing the production conditions.

All samples exhibit a distinct reduction in electrical conductivity within the initial third of the sample, aligning with the transitional region between the base metal (BM) and the HAZ. This underscores the importance of understanding the transitional zones during FSP.

The purpose of the present work is to improve the industry performance by identifying and quantifying the risks faced by the Indian pharmaceutical industry (IPI). The risk values for the prominent risks and overall industry are determined based on the four risk parameters, which would help determine the most contributive risks for mitigation.

An extensive literature survey was done to identify the risks, which were also validated by industry experts. The finalized risks were then evaluated using the fuzzy synthetic evaluation (FSE) method, which is the most suitable approach for the risk assessment with parameters having a set of different risk levels.

The three most contributive sub-risks are counterfeit drugs, demand fluctuations and loss of customers due to partners' poor service performance, while the main risks obtained are demand, financial and logistics. Also, the overall risk value indicates that the industry faces medium to high risk.

The study identifies the critical risks which need to be mitigated for an efficient industry. The industry is most vulnerable to the demand risk category. Therefore, the managers should minimize this risk by mitigating its sub-risks, like demand fluctuations, bullwhip effect, etc. Another critical sub-risk, the counterfeit risk, should be managed by adopting advanced technologies like blockchain, artificial intelligence, etc.

There is insufficient literature focusing on risk quantification. Therefore, this work addresses this gap and obtains the industry's most critical risks. It also discusses suitable mitigation strategies for better industry performance.

The objective of this research is to examine the connections between mindfulness, psychological empowerment and the manifestation of ostracism in the workplace, particularly instigated ostracism, among university professors.

The study relies on data from 746 professors from a renowned university located in northern India. The researchers utilized pre-established scales to measure latent variables, and a seven-point Likert scale for evaluation purposes. The data were analyzed using PLS-SEM.

The results indicate a positive correlation between mindfulness and psychological empowerment, explaining 42.20% of its variance. Additionally, a negative correlation between psychological empowerment and workplace ostracism is observed, accounting for 1.70% and 5.20% of their variances, respectively. These findings suggest associations but do not imply causality, highlighting the need for further research to explore these relationships.

Its focus on university professors limits the study’s insights from a specific region, potentially affecting the findings' generalizability. Future research should encompass a broader demographic and geographic range to enhance the applicability and relevance of the results across diverse academic contexts.

This study contributes to the existing literature by highlighting a correlation between mindfulness and perceived psychological empowerment among university professors. It also suggests a potential association between psychological empowerment and reduced perceptions of the workplace and instigated ostracism. These preliminary findings, while not indicative of causality, could inform future research and the development of policies promoting mindfulness and empowerment in academic environments.

This study examines the correlations between mindfulness, psychological empowerment and ostracism within academic settings. It uniquely highlights the positive correlation between mindfulness and psychological empowerment and how this relates to reduced perceptions of workplace ostracism among university faculty. These findings suggest that universities could enhance work environments by focusing on these areas, potentially enriching higher education management practices.

An integrated intuitionistic fuzzy (IF) modelling-based framework for examining the performance analysis of a packaging unit (PU) in three different stages has been proposed.

For the series and parallel configuration of PU, a mathematical model based on the intuitionistic fuzzy Lambda–Tau (IFLT) approach was developed in order to calculate various reliability parameters at various spreads. For determining membership and non-membership function-based reliability parameters for the top event, AND/OR gate transitions expression was employed.

For 15%–30% spread, unit’s availability for the membership function falls by 0.006442%, and it falls even more by 0.014907% with an increase in spread from 30% to 45%. In contrast, for 15%–30% spread, the availability of non-membership function-based systems reduces by 0.007491% and further diminishes. Risk analysis has presented applying an emerging approach called intuitionistic fuzzy failure mode and effect analysis (IFFMEA). For each of the stated failure causes, the output values of the intuitionistic fuzzy hybrid weighted Euclidean distance (IFHWED)-based IFFMEA have been tabulated. Failure causes like HP1, MT6, FB9, EL16, DR23, GR27, categorized under subsystems, namely hopper, motor, fluidized bed dryer, distributor, grader and bin, respectively, with corresponding IFFMEA output scores 1.0975, 1.0190, 0.8543, 1.0228, 0.9026, 1.0021, were the most critical one to contribute in the system’s failure.

The limitation of the proposed framework lies in the fact that the results obtained for both reliability and risk aspects mainly depend on the correctness of raw data provided by the experts. Also, an approximate model of PU is obtained from plant experts to carry performance analysis, and hence more attention is required in constructing the model. Under IFLT, reliability parameters of PU have been calculated at various spreads to study and analyse the failure behaviour of the unit for both membership and non-membership function in the IFS of [0.6,0.8]. For both membership- and non-membership-based results, availability of the considered system shows decreasing trend. To improve the performance of the considered system, risk assessment was carried using IFFMEA technique, ranking all the critical failure causes against IFHWED score value, on which more attention should be paid so as to avoid sudden failure of unit.

The livelihood of millions of farmers and workers depends on sugar industries. So perpetual running of these industries is very important from this viewpoint. On the basis of findings of reliability parameters, the maintenance manager could frame a correct maintenance policy for long-run availability of the sugar mills. This long-run availability will generate revenue, which, in turn, will ensure the livelihood of the farmers.

Mathematical modelling of the considered unit has been done applying basic expressions of AND/OR gate. IFTOPSIS approach has been implemented for ranking result comparison obtained under IFFMEA approach. Eventually, sensitivity analysis was also presented to demonstrate the stability of ranking of failure causes of PU.

To meet energy demand and tackle the challenges posed by global warming, Bagasse-based Cogeneration Power Generation (BCPG) plant in sugar mills have tremendous potential due to large-scale supply of renewable fuel called bagasse. To meet this goal, an integrated framework has been proposed for analyzing performance issues of BCPG.

Intuitionistic Fuzzy Lambda-Tau (IFLT) approach was implemented to compute various reliability parameters. Intuitionistic Fuzzy Failure Mode and Effect Analysis (IF-FMEA) approach has been implemented for studying risk issues results in decrease in plant's availability. Moreover, IF- Technique for Order Performance by Similarity to Ideal Solution (IF-TOPSIS) is implemented to verify accuracy of IF-FMEA approach.

For membership and non-membership functions, availability decreases to 0.0006% and 0.0020% respectively for spread ±15% to ±30%, and further decreases to 0.0127% and 0.0221% for spread ±30% to ±45%. Under risk assessment failure causes namely Storage tank (ST3), Valve (VL6), Transfer pump (TF8), Deaerator tank (DT11), High pressure heater and economiser (HP15), Boiler drum and super heater (BS22), Forced draft and Secondary air fan (FS25), Air preheater (AH29) and Furnace (FR31) with Intuitionistic Fuzzy Hybrid Weighted Euclidean Distance (IFHWED) based output scores – 0.8988, 0.9752, 0.9400, 0.8988, 0.9267, 1.1131, 1.0039, 0.8185, 1.0604 were identified as the most critical failure causes.

Reliability and risk analysis results derived from IFLT and IF-FMEA approaches respectively, to address the performance issues of BCPG is based on the quantitative and qualitative data collected from the industrial experts and maintenance log book. Moreover, to take care of hesitation in expert's knowledge, IF theory-based concept is incorporated so as to achieve more accuracy in analysis results. Reliability and risk analysis results together will be helpful in analyzing the performance characteristics and diagnosis of critical failure causes, which will minimize frequent failure in BCPG.

The framework will help plant managers to frame optimal maintenance policy in order to enhance the operational aspects of the considered unit. Moreover, the accurate and early detection of failure causes will also help managers to take prudent decision for smooth operation of plant.

The results obtained ensure continuous operation of plant by utilizing the bagasse as fuel in boiler and also mitigate the wastages of fuel. If this bagasse (green fuel) is not properly utilized, there remains a dependency on coal-based power plants to meet the power demand. The results obtained are useful for decreasing dependency on coal, and promoting bagasse as the green, and alternative fuel, the emission by burning of these fuels are not harmful for environment and thereby contribute in preventing the environment from harmful effect of GHGs gases.

IFLT approach has been implemented to develop reliability modeling equations of the BCPG unit, and furthermore to compute various reliability parameters for both membership and non-membership function. The ranking results of IF-FMEA are compared to IF-TOPSIS approach. Sensitivity analysis is done to check stability of proposed framework.

This study aims to identify, analyze and rank the critical success factors (CSFs) of Lean Six Sigma (LSS) implementation in Indian manufacturing sector based micro, small and medium enterprises (MSMEs). This study provides critical insight for managers and researchers aspiring for successful implementation of LSS in Indian manufacturing MSMEs.

The CSFs were extracted from literature followed by a questionnaire-based survey from 120 industry professionals with extensive knowledge and experience about LSS working in Indian manufacturing MSMEs. Further, the CSFs were grouped based on their fundamental relevance and ranked using best worst method (BWM) approach using inputs from LSS experts.

This study provides insights on success factors that have helped Indian manufacturing MSMEs to implement LSS. The findings signify that “Strategy based CSFs” were ranked as the top most important factors, followed by two other category factors namely “Bottom-Line CSFs” and “Supplier based and other category-based CSFs”.

The proposed research is specifically relevant to the context of MSMEs in the Indian manufacturing sector. In the future, the same approach can be extended to a global context, encompassing service sector-based MSMEs in healthcare and finance.

This study provides valuable inputs for managers, decision-makers, industrial practitioners and researchers about Indian manufacturing MSMEs. The identified CSFs and their prioritization offer a roadmap for successful adoption of LSS. Managers can allocate resources, and make strategic decisions based on the prioritized CSFs. Decision-makers can align their initiatives with the identified CSFs. Industrial practitioners gain insights to enhance their LSS initiatives, and researchers can focus their efforts on areas critical to LSS implementation in Indian MSMEs. Furthermore, the structured approach employed in this study can be adopted by various MSME sectors globally, thereby broadening the comprehension of LSS implementation.

This study contributes to the existing body of knowledge by addressing the gaps in literature on CSFs related to LSS adoption within Indian manufacturing MSMEs. While LSS has been widely studied, there is limited focus on its adoption in the context of Indian MSMEs. The combination of extensive literature review, questionnaire-based survey and the application of the BWM approach for prioritizing CSFs adds originality to the research.

The purpose of this study is to present the systematic literature review (SLR) on Lean Six Sigma (LSS) by exploring the state of the art on growth of literature on LSS within the manufacturing sector, critical factors to implement LSS, the role of LSS in the manufacturing sector from an implementation and sustainability viewpoint and Industry 4.0 viewpoints while highlighting the research gaps.

An SLR of 2,876 published articles extracted from Scopus, WoS, Emerald Insight, IEEE Xplore, Taylor & Francis, Springer and Inderscience databases was carried out following the protocol of systematic review. In total, 154 articles published in different journals over the past 10 years were selected for quantitative and qualitative analysis which revealed a number of research gaps.

The findings of the SLR revealed the growth of literature on LSS within the manufacturing sector. The review also highlighted the most cited critical success factors, critical failure factors, performance indicators and associated tools and techniques applied during LSS implementation. The review also focused on studies related to LSS and sustainability viewpoint and LSS and Industry 4.0 viewpoints.

The findings of this SLR can help senior managers, practitioners and researchers to understand the current developments and future requirements to adopt LSS in manufacturing sectors from sustainability and Industry 4.0 viewpoints.

Academic publications in the context of the role of LSS in various research streams are sparse, and to the best of the authors’ knowledge, this paper is one of the first SLRs which explore current developments and future requirements to implement LSS from sustainability and Industry 4.0 perspective.

This study aims to investigate the impact of customer perceptions of Augmented Reality (AR) attributes such as augmentation, interactivity and vividness on attitudes towards AR mobile apps, virtual product and behavioural intentions. Also, the mediation role of customer engagement in the effect of perceptions of AR attributes on attitudes and behavioural intentions is examined using the Theory of Interactive Media Effects.

The study used a cross-sectional design. A total of 456 valid data were collected from the Millennials and Generation Z cohorts using purposive sampling. The conceptual framework was assessed using Partial Least Squares-Structural Equation Modelling (PLS-SEM) and Partial Least Squares-Multi Group Analysis (PLS-MGA).

The research revealed that customer perceptions of AR features such as augmentation, interactivity and vividness significantly influenced customer engagement, leading to favourable attitudes towards both the AR mobile app and the Virtual product as well as behavioural intentions. Furthermore, the study substantiates the role of customer engagement as a mediator in the relationship between customer perceptions of AR attributes and both attitudinal and behavioural outcomes.

To the best of the authors’ knowledge, this is the first attempt to investigate the significance of perceived augmentation as an antecedent to customer engagement and the mediating role of customer engagement on the influence of perceptions of AR attributes on attitudinal and behavioural intention.

More than 40% of Indian households still rely on unclean cooking fuels, exposing particularly women and children to adverse health effects. This paper explores the factors determining a household’s cooking fuel choice in India.

The study used the fifth round of the National Family Health Survey (2019-21) dataset. A chi-square test and a logistic regression were used for empirical analysis. Cooking fuel was categorized as “clean” and “unclean” cooking fuel.

The result shows that around 47% of the households are still using unclean cooking fuel in India. Households with a better-educated or female head, those with smaller family sizes, those with a higher level of wealth and those located in urban areas are more likely to use clean cooking fuel. Similarly, households headed by younger individuals and Muslim households are linked to more usage of clean cooking fuels. However, Scheduled Tribe (ST) and Other Backward Classes (OBC) households and those headed by older individuals are less likely to use clean cooking fuels.

The cross-sectional nature of data enables us to draw only associations between the variables and not causal relationships between them. The findings of this study have important implications for household energy policies in India and other developing nations. There is a need for policymakers to seriously consider socioeconomic factors in addressing issues and challenges associated with household energy consumption.

The study extends the empirical literature on determinants of household cooking fuel choice using the latest round of National Family Health Survey data from India.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2023-0988