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This paper aims to analyze the present trends in pharmaceutical innovation and the impact of generic competition.

A secondary research was conducted to collect data related to new drug approvals of various classes over previous years; trends of investment in research and development; and the pipeline of new drug products of pharmaceutical companies.

While the new molecular entity (NME) approval rate has not improved over previous years, innovators have been aggressively pursuing the radical innovation process. Further, there has been a significant increase in incremental innovation. Pharmaceutical companies' investment in research has gone up resulting in higher number of application for new drug approvals. In India, pharmaceutical companies have significantly increased their research investment. However, the NME pipeline is still slim though there has been a significant surge in generic filings.

It provides a concise understanding of trends in pharmaceutical innovation and analyzes how various factors are shaping up the innovation process. It also throws light on the evolution story of Indian pharmaceutical companies to become drug innovators.

The study explores the role of dialogic public communication and information quality (IQ) in evaluating the operational performance of donation-based crowdfunding (DBC) tasks. These tasks are primarily used to support disaster relief operations. The authors also test the influence of cognitive trust and swift trust as moderating variables in explaining the relationship between both IQ and dialogic communication with operational performance.

The authors used a primary survey to test the hypotheses. A total of 203 responses were collected from multiple crowdfunding platforms. The authors used archival data from task creators on donation-based crowdfunding platforms, and a structured questionnaire is also used to collect responses. Data are analyzed using Warp PLS 6.0. Warp PLS 6.0 works on the principle of partial least square (PLS) structured equation modeling (SEM) and has been used widely to test path analytical models.

The authors found out that the operational performance is explained significantly by the quality of information and its association with dialogic public communication. The results support the arguments offered by dialogic public communication theory and trust transfer theory in assessing the operational success of DBC. The study also confirms that cognitive trust positively moderates the relationship between IQ and organizational public dialogic communication and operational performance. It is also revealed that the duration of the DBC task has no significant control over dialogic public communication.

The study lays practical foundations for task creators on DBC platforms and website designers as it sets the importance of both IQ and dialogic communication channels. The communication made by the task creator and/or the DBC platforms with the donors and potential donors in the form of timely and appropriate information forms the key to the success of any DBC task. The study also helps task creators choose a suitable platform to improve performance.

The authors propose a unique framework by integrating two theoretical perspectives: dialogic public relation theory and trust transfer theory in understanding the operational performance of donation-based crowdfunding tasks. The authors address DBC tasks catering to disaster relief operations by collecting responses from task creators on DBC platforms. The study uniquely positions itself in the area of information and communication.

The study presents various barriers to adopt big data analytics (BDA) for sustainable manufacturing operations (SMOs) post-coronavirus disease (COVID-19) pandemics. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the graph theory matrix approach (GTMA) is applied.

The study presents various barriers to adopt BDA for the SMOs post-COVID-19 pandemic. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the GTMA is applied.

The study identifies barriers to investment in BDA implementation. It categorizes the barriers based on factor analysis and computes the intensity for each category of a barrier for BDA investment for SMOs. It is observed that the organizational barriers have the highest intensity whereas the human barriers have the smallest intensity.

This study may help organizations to take strategic decisions for investing in BDA applications for achieving one of the sustainable development goals. Organizations should prioritize their efforts first to counter the barriers under the category of organizational barriers followed by barriers in data management and human barriers.

The novelty of this paper is that barriers to BDA investment for SMOs in the context of Indian manufacturing organizations have been analyzed. The findings of the study will assist the professionals and practitioners in formulating policies based on the actual nature and intensity of the barriers.

With gaining popularity, online communities are increasing. It is leading to the data and information overflow. So, there are some challenges like cyber frauds, cyberbullying, etc. while engaging with online communities. Not only this, anonymity of the participants, stress and racism are also big challenges in online communities' interaction. Online harassers' attack tactics have changed over time. In addition, there are challenges like quality of discussion, inequality in participation of the users, etc. may scale online communities towards incitement and activism. Therefore, this study will try to analyse these challenges for overall benefit of the society.

The underlying fuzzy set theory is employed to handle the fuzziness of users' perceptions since the attributes are expressed in linguistic preferences. Through exhaustive literature review, the authors have identified 15 challenges. These challenges are further categorised as cause and effect by using DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach.

Lack of strategic planning and uninspired discussions between users has emerged as a major challenge in cause category. This study further demonstrates how individual challenge can be managed and developed to navigate the online communities to maintain a healthy environment in society.

Results are based on limited dataset. Therefore, findings cannot be generalised for all online communities.

The research findings offer a suitable direction to policymakers to formulate and design policies, laws and regulations to increase user engagement in the online community. The study is beneficial to firms and researchers in understanding the factors influencing effective management of online communities.

The purpose of this paper is to examine the indirect effects of nutritional knowledge and attitude toward food label use on food label use through self-efficacy and trust, as well as whether gender moderates this relationship.

A sample of Indian adults with multiple chronic conditions was surveyed about their nutritional knowledge, attitude, self-efficacy and use of food labels. Hypotheses were tested using Hayes’s (2013) PROCESS macro for SPSS.

The results show that nutritional knowledge and attitude toward food label use positively predict food label use through self-efficacy and trust. However, these mediation effects are moderated by gender such that the indirect relationship is stronger among men than women.

Food marketers and government agencies engaged in nutrition education campaigns should aim to increase patients’ confidence in comprehending food label information.

Since food labels can be a valuable tool to help patients with chronic diseases to make informed decisions about their diet and lifestyle, regulators may consider mandating nutritional labels on foods to help them improve their food or dietary choices.

This study uniquely applies Fisher and Fisher’s (1992) information–motivation–behavioral skills model as a theoretical framework to examine the influence of nutrition knowledge and attitude toward food label use on food label usage of Indian patients with multiple chronic diseases.

This paper aims to study the concept, characteristics and factors of the resilient supply chain (RSC) and develop a hierarchical structural model and classify the factors based on their interrelationships.

This paper has used a mixed-approach of literature review and expert opinion to identify the factors of RSC. For the development of the structural model and clustering of the factors, this paper has used the total interpretive structural modeling approach with Matrice d’Impacts Croises-Multiplication Applique and Classment and decision-making trial and evaluation laboratory analysis.

In total, this study has identified 17 factors that enable the 3R capability of the RSC. The result shows that the factors have a close dependence relationship with supply chain (SC) risk management culture as the most influencing factor. Further, this study classifies the factors into enablers and strategies.

This research work is the theoretical contribution to the RSC concept and helps the experts to develop and improve the resilient ability in the SC. This research is based entirely on subjective expert feedback; thus, the results are sensitive to the expert’s judgment.

This research will help the decision-makers in allocating the resources and policies to develop or improve the SC capabilities.

This research work is the first kind of research in the field of the RSC that considers the 3R concept to identify and model the resilient factors of the SC. Along with the theoretical concept, this research provides empirical evidence for the importance ranking of the factors.

Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken systematically with the utmost transparency. The purpose of this paper is to construct capital procurement decision-making model to optimize supplier selection in the Indian automobile industry.

To achieve the stated objective, a combined approach of fuzzy theory and AHP-DEMATEL is applied. Evaluation parameters are identified through an extensive literature review and criteria validation has been introduced through a Fuzzy Delphi method by using fuzzy linguistic scales to handle the vagueness of information. AHP is employed to find the priority weight of criteria, although an inter-relationship map among criteria is not possible through AHP alone since it considers all criteria as independent. To overcome this, DEMATEL is used to establish cause-effect relationships among criteria.

The results show that the total cost of ownership (TOC) is the first weighted criterion in supplier selection for capital procurement, followed by manufacturing flexibility and maintainability, then conformity with requirement. The cause-effect model shows that supplier profile, TOC, service support and conformity with requirement are in the cause group and are considered to be the most critical factors in selecting the supplier.

The study’s outcome can help the automobile industry to optimize their selection process in selecting their suppliers for capital procurement; the proposed model can provide guidelines and direction in this regard.

Industries start focusing on the green concept in supply chain management (SCM) to reduce waste and emission, preserve the quality of natural resources and decrease the consumption of hazardous/harmful materials for better product life cycle, which not only improve environmental performance but also economic performance. But, for industries, it is still very difficult to understand and analyze the effect of individual activities and their corresponding contribution. The purpose of this paper is to identify and analyze selected issues in green supply chain management for the implementation of the green concept in industries.

To fulfill the objectives of this paper, analytical network process-multi-objective optimization using rational analysis (ANP-MOORA) techniques are used. In the proposed methodologies, different issues, sub-issues, and alternatives are identified for the selection of the best supply chain using ANP which is being followed by the MOORA method.

Findings of this paper are highly valuable for the Indian manufacturing industries for the management of green supply chain (GSC) issues.

In this research, only selected issues are identified and analyzed for the management of GSCs. Further, it is believed that an ANP-based framework helps to take up the explicit account of multi-criteria decision making (MCDM) approaches in decision making and for improving and selecting the best supply chain. Other issues in GSC can be analyzed and further extended by other MCDM approaches.

This paper identified different type of supply chains and their issues. The systematic way of analyzing the green concept in supply chain helps the researchers and managers to implement green management practices for improving economic and environmental performance.

Outsourcing has become a strategic decision for most of the organizations in the present context of globalization and circular economy. The objective of proposed study is to empirically investigate the relationship between the outsourcing benefits and triple bottom line (TBL)-based performance of reverse supply chain (RSC) comprising of economic, environmental and social factors.

In the present study, the partial least square path approach of structural equation modeling has been applied for testing hypotheses. A questionnaire was developed for collecting the information and responses from the experts of electronics industry, India. Measurement models were tested for ensuring the fitness of data for further applying partial least square path approach of SEM.

The results provide insightful information on outsourcing and RSC performance. It reveals that outsourcing decisions are important and have great influence on the economic, environmental and social performance of RSC.

The study will provide useful guidance to the organizations for outsourcing decisions. One of the limitations of the study is that it has considered data collected from the Indian electronics industry. Therefore, results may not be generalized.

The third-party service providers have core competencies, and they are the experts of providing RSC services. It is also apparent from the exploration of past research and theoretical background that there are limited number of studies focusing on the impact of outsourcing decisions in RSC performance specifically from the TBL perspective. Hence, the proposed study is an effort to explore the impact of outsourcing RSC activities on the performance of RSC from a sustainability perspective.

The purpose of this paper is to investigate the potential synergy between companies’ sustainable supply chain management (SSCM) activities and their supply chain resilience (SCRES). The authors propose hypotheses about the impact of buying companies SSCM activities on the inflicted damage by unexpected supply chain disruptions and the recovery time afterwards and test these empirically using data from companies during the global COVID-19 pandemic.

The authors investigate a sample of 231 of the largest publicly traded companies in the European Union with 4.158 firm-year observations. For the analysis, the authors generate variables capturing the companies’ intensity and years of experience of their SSCM activities targeted at the supply chain and run regression analyses on the inflicted damage due to the COVID-19 pandemic and the recovery time after the disruption.

Buying companies’ SSCM activities have a positive effect on their SCRES. The damage inflicted by unexpected supply chain disruptions is lower when companies have higher levels of SSCM and longer experience with it. The recovery time afterwards is significantly reduced by longer experience with SSCM efforts.

The authors suggest SCRES is reinforced by transparency, situational awareness, social capital and collaboration resulting from companies SSCM activities translate into increased SCRES.

The authors show that companies with superior SSCM are more resilient in a crisis and conclude that, therefore, companies should invest in SSCM to prevent future supply disruptions.

To the best of the authors’ knowledge, this is the first empirical study analyzing a data set of multi-industry companies, linking their SSCM activities to SCRES during the pandemic.