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This paper aims to examine the effect of three types of health-related claims (health, nutrition and ingredient) and product healthiness on situational skepticism toward the claims that appear on the front-of-package of food products. The effect of situational skepticism on the purchase intention of the product is further examined.

Two experimental studies were conducted with a 3 (health-related claims: health claim vs nutrition claim vs ingredient claim) × 2 (product healthiness: healthy vs unhealthy) between-subjects factorial design. Study 1 investigates the effects within a single product category (Biscuits) and Study 2 the effects across product categories (Salad and Pizza).

The results demonstrate that situational skepticism is the highest for health claims, followed by nutrition claims and the least for ingredient claims. In addition, situational skepticism is higher for claims appearing on unhealthy products vis-à-vis healthy ones. Finally, situational skepticism mediates the relationship between claim type, product healthiness and product purchase intention.

This study contributes to the field of nutrition labeling by advancing research on information processing of nutrition labels through the lens of the persuasion knowledge model (Friestad and Wright, 1994). Specifically, this study contributes to a nuanced understanding of claim formats on how the language properties of the claim – its vagueness, specificity and verifiability – can affect consumer perception. This study finds that higher specificity, verifiability and lower vagueness of ingredient claims lead to lower skepticism and hence higher purchase intention.

Furthermore, this study incrementally contributes to the ongoing discussion about the claim–carrier combination by showing that health-related claims are better perceived on healthy compared to unhealthy products. Hence, managers should avoid health washing, as this can backfire and cause harm to the reputation of the firm.

From a public policy point of view, this study makes a case for strong monitoring and regulations of ingredient claims, as consumers believe these claims easily and hence can be misled by false ingredient claims made by unethical marketers.

The scope of research on skepticism has largely been limited to examining a general individual tendency of being suspicious (i.e. dispositional skepticism) in health-related claims as well as other areas of marketing. In this research, the authors extend the scope by examining how specific types of claims (health vs nutrition vs ingredient) and product healthiness jointly impact consumer skepticism, i.e. situational skepticism.

Owing to highly volatile and chaotic external events, predicting future movements of cryptocurrencies is a challenging task. This paper advances a granular hybrid predictive modeling framework for predicting the future figures of Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), Stellar (XLM) and Tether (USDT) during normal and pandemic regimes.

Initially, the major temporal characteristics of the price series are examined. In the second stage, ensemble empirical mode decomposition (EEMD) and maximal overlap discrete wavelet transformation (MODWT) are used to decompose the original time series into two distinct sets of granular subseries. In the third stage, long- and short-term memory network (LSTM) and extreme gradient boosting (XGB) are applied to the decomposed subseries to estimate the initial forecasts. Lastly, sequential quadratic programming (SQP) is used to fetch the forecast by combining the initial forecasts.

Rigorous performance assessment and the outcome of the Diebold-Mariano’s pairwise statistical test demonstrate the efficacy of the suggested predictive framework. The framework yields commendable predictive performance during the COVID-19 pandemic timeline explicitly as well. Future trends of BTC and ETH are found to be relatively easier to predict, while USDT is relatively difficult to predict.

The robustness of the proposed framework can be leveraged for practical trading and managing investment in crypto market. Empirical properties of the temporal dynamics of chosen cryptocurrencies provide deeper insights.

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.

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

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 study is aimed at analyzing the perceptions of students and teachers regarding the effectiveness of massive open online courses (MOOCs) on learning efficiency of students and also evaluating MOOCs as an ideal tool for designing a blended model for education.

The analysis was carried out by using the data gathered from the students as well as teachers of University of Mysore, Karnataka, India. Two separate sets of questionnaires were developed for both the categories of respondents. Also, the respondents were required to have prior experience in MOOCs. Further, the collected data was analyzed using statistical package for social sciences (SPSS).

The study showed that MOOCs have a more positive influence on learning efficiency, as opined by both teachers and students. Negative views such as cheating during the assessment, lack of individual attention to students and low teacher-student ratio were also observed.

Many educational institutions view that the MOOCs do not influence learning efficiency and also do not support in achieving their vision. However, this study provides evidence that MOOCs are positively influencing the learning efficiency and also can be employed in a blended model of education so as to promote collaborative learning.

Technology is playing a pivotal role in all fields of life and the education sector is not an exception. It can be rightly said that the technology-based education models such as MOOCs are the need of the hour. This study may help higher education institutions to adopt MOOCs as part of their blended model of education, and, if already adopted, the outcome of the present study will help them to improve the effectiveness of the MOOCs they are offering.

Opportunistic and delayed maintenances are increasingly becoming important strategies for sustainable maintenance practices since they increase the lifetime of complex systems like aircrafts and heavy equipment. The objective of the current study is to quantify the optimal time window for adopting these strategies.

The current study considers the trade-offs between different costs involved in the opportunistic and delayed maintenances (of equipment) like the fixed cost of scheduled maintenances, the opportunistic rewards that may be earned and the cost of premature parts replacement. The probability of the opportunistic maintenance has been quantified under two different scenarios – Mission Reliability and Renewal Process. In the case of delayed maintenance, the cost of the delayed maintenance is also considered. The study uses optimization techniques to find the optimal maintenance time windows and also derive useful insights.

Apart from finding the optimal time window for the maintenance activities the study also shows that opportunistic maintenance is beneficial provided the opportunistic reward is significantly large; the cost of conducting scheduled maintenance in the pre-determined slot is significantly large. Similarly, the opportunistic maintenance may not be beneficial if the pre-mature equipment parts replacement cost is significantly high. The optimal opportunistic maintenance time is increasing function of Weibull failure rate parameter “beta” and decreasing function of Weibull failure rate parameter “theta.” In the case of optimal delayed maintenance time, these relationships reverse.

To the best of our knowledge, very few studies exist that have used mission reliability to study opportunistic maintenance or considered the different cost trade-offs comprehensively.

The purpose of this paper is to examine the restructuring of human resources development processes in Indian Institutes of Technology (IIT) libraries in North India, emphasizing the essential information and communications technology (ICT) skills for both recruits and existing staff.

The study used a survey research design, with two different sets of structured questionnaires used to collect data. The first set, which was distributed to all heads of seven IIT libraries in North India, received a 100% response rate. Simultaneously, the second set was distributed to library users, yielding a 92% response rate (680 responses out of 700 distributed). The collected data were analyzed and tabulated, with suitable interpretations.

The findings of the study reveal that all examined libraries have implemented skill development programs. Moreover, advanced ICT skills are considered essential for staff appointments, and specific institutes (IIT Kanpur, IIT Delhi, IIT Jodhpur and IIT Ropar) took the initiative to provide ICT training to their employees. Trained employees exhibited enhanced performance, attributed to advanced ICT knowledge. The study suggests restructuring selection criteria and introducing structured ICT training programs for library staff, ensuring a more adept workforce for current demands.

The study can increase the impact globally on human resource development by incorporating soft skills, job satisfaction and leadership development while exploring research opportunities through cross-institutional comparisons and the integration of emerging technologies such as artificial intelligence and virtual reality.

This study collected primary data from IIT libraries in North India using self-designed questionnaires. The findings provide useful insights into how libraries might restructure human resource development in the digital age.

This paper aims to critically review the isolation and chemistry of plant pigments.

A literature survey from 1974 to 2022 was carried out and studied thoroughly. The authors reviewed literature in various areas such as isolation methods and catalytic properties of pigments.

With vast growing research in the field of catalytic activities of various pigments like chlorophyll, anthocyanin and flavonoids, there is still scope for further research for the pigments such as Lycopene, carotenoids and xanthophyll as there has not been any significant work in this area.

Plant pigments may be used as an ecofriendly catalyst for chemical reactions.

One can get the direction of pigment research.

Plant pigments are natural and ecofriendly catalyst which can reduce the pollution.

This is an original work. This paper precisely depicts the advantages as well as disadvantages of the isolation techniques of pigments. This study also presents the chemistry of plant pigments.

This study aims to examine the enablers of productivity of enterprise-level Agile development process using modified total interpretative structural modeling (TISM). The two main objectives of the current study are to determine the variables influencing enterprise-level agile development productivity and to develop modified TISM for the corresponding components.

To identify enablers of the productivity of enterprise-level agile software development process a literature review and opinions of domain experts were collected. A hierarchical relationship among variables that show direct and indirect influence is created using the modified TISM (M-TISM) technique with Cross Impact Matrix-Multiplication Applied to Classification analysis. This study examined and analyzed the relationships between the determinants within the enterprise using a M-TISM technique.

With the literature review, the study could identify ten enabling factors of the productivity of Agile development process at the enterprise level. Results depict that program increment (PI) planning and scalable backlog management, continuous integration and continuous delivery (CI/CD), agile release trains (ART), agile work culture, delivery excellence, lean and DevOps practices, value stream mapping (VMS), team skills and expertise, collaborative culture, agile coaching, customer engagement have an impact on the productivity of enterprise-level Agile development process. The results show that team collaboration, agile ways of working and customer engagement have a greater impact on productivity improvement for enterprise-level Agile development process.

The developed model is useful for organizations employing scaled Agile development processes in software development. This study provides a recommended listing of key enablers, that may enable productivity improvements in the Agile development process at the enterprise level. Strategists should focus on team collaboration and Agile project management. This study offers a modified TISM model to academicians to help them understand the effects of numerous variables on maintaining the productivity of an enterprise-level Agile. The identified characteristics and their hierarchical structure can help project managers during the execution of Agile projects at the enterprise level, more effectively, increasing their success and productivity.

The study addresses the gap in the literature by interpretative relationships between the identified enabling factors. The model validation is carried out by a panel of nine experts from several information technology organizations deploying Agile software development at the enterprise level. This unique method broadens the knowledge base in Agile software development at scale and provides project managers and practitioners with a practical foundation.