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The purpose of this study is to explore circular economy (CE) initiatives and apply the stimulus-organism-response theory to find the socio-political drivers and enablers of CE in the pharmaceutical industry. CE as a concept was relatively not studied much with respect to socio-political interests from operations management perspectives. This was especially so in the pharmaceutical industry.

This research study was anchored in the theoretical conversation of stimulus-organism-response theory to find the socio-political interests and enablers of the regenerative CE principles. These were the functions of remanufacturing, reuse and recycle. For this research study, data was collected in two steps. First, eight industry practitioners were interviewed to understand the CE practices in the pharmaceutical industry. Then 166 chiefs of production and operations functions from 124 pharmaceutical companies were surveyed. The quantitative data was empirically analyzed using SmartPLS3 software.

This research study revealed that pressure from suppliers and other public stakeholders were driving regenerative CE practices in the pharmaceutical industry. The results further stated that CE enablers such as green information technology systems and internal environmental management were critical for making pharmaceutical manufacturing operations circular.

This research study measured the constructs on a formative scale. Studies measuring socio-political interests, CE enablers and sustainability practices constructs on a formative scale were much required for the development of the CE theory. This research study output could be applied across geographies and industries to measure the indicators of CE.

This research study indicated that in the context of the pharmaceutical industry, there was an overemphasis on the remanufacture and reuse principles. However, the focus on recycling principles was mostly subdued. For managers and regulators in the pharmaceutical sector, this research study provided clear insights that for more effective CE implementation. This was based on an effective application of recycling practices in the critical functions in pharmaceutical industry.

Earlier research studies on green and environmental manufacturing were focused on linear production models. To provide clear and robust foundations for CE theory, this research study considered operations management from the perspective of the value chain. This comprised the entire circular production model. Earlier research studies had treated socio-political interests, CE enablers and sustainability practices as reflective constructs. This study was one of the foremost to measure these constructs on a formative scale.

The purpose of this study was to comprehend the current state of green supply chain management (GSCM) and its drivers and enablers in the pharmaceutical supply chains (PSCs).

This study developed a model consisting of the factors green drivers, green enablers and green practices. For this study, data were collected from 166 supply chain heads from 124 pharmaceutical companies operating in India. The data was empirically analysed using SmartPLS3 software.

The study revealed that in Indian PSCs, public pressure, supplier pressure and competitor pressure were the major drivers for GSCM practices and coercive pressures such as pressure from government and regulatory bodies were insignificant drivers. The results indicated that the influence of green drivers and green enablers altered with supply chain flow. Green drivers indicated higher influence at the upstream of PSCs whereas the influence of green enablers was higher at the downstream of PSCs. Furthermore, the study revealed that the factor “green enablers” was a good mediator for the relationship between “green drivers” and “GSCM practices” in PSCs.

This study was an extension work with the addition of external green drivers to the self-induced organizational activities. Further investigations can be done by including the “green barriers” construct in the conceptual model.

This research connected the institutional theory with the resource-based view to understanding the role of green drivers and green enablers in greening PSC. For managers and regulators, this study provided clear insights on how to approach different supply chain drivers and enablers to maximize the impact of GSCM practices. Moreover, the findings of this study helped in incorporating knowledge about GSCM into a framework that can be used for defining strategies for setting up a sustainable PSC for pharmaceutical products leading to the development and growth of the pharmaceuticals industry.

Most of the earlier studies on GSCM were at the firm level and some studies were at the supply chain level. To further enhance the scope of GSCM theory, this study was conducted at two different levels, first at the complete supply chain level and second at three different levels: upstream, firm-level and downstream.

The purpose of this research study was to understand the simultaneous competitive and social gains of machine learning (ML) and artificial intelligence (AI) usage in organizations. There was a knowledge hiatus regarding the contribution of the deployment of ML and AI technologies and their effects on organizations and society.

This study was grounded on the dynamic capabilities (DC) and ML and AI automation-augmentation paradox literature. This research study examined these theoretical perspectives using the response of 239 Indian organizational chief technology officers (CTOs). Partial least square-structural equation modeling (PLS-SEM) path modeling was applied for data analysis.

The results indicated that ML and AI technologies organizational usage positively influenced DC initiatives. The findings depicted that DC fully mediated ML and AI-based technologies' effects on firm performance and social performance.

This study contributed to theoretical discourse regarding the tension between organizational and social outcomes of ML and AI technologies. The study extended the role of DC as a vital strategy in achieving social benefits from ML and AI use. Furthermore, the theoretical tension of the automation-augmentation paradox was explored.

Organizations deploying ML and AI technologies could apply this study's insights to comprehend the organizational routines to pursue simultaneous competitive benefits and social gains. Furthermore, chief technology executives of organizations could devise how ML and AI technologies usage from a DC perspective could help settle the tension of the automation-augmentation paradox.

Increased ML and AI technologies usage in organizations enhanced DC. They could lead to positive social benefits such as new job creation, increased compensation to skilled employees and greater gender participation in employment. These insights could be derived based on this research study.

This study was among the first few empirical investigations to provide theoretical and practical insights regarding the organizational and societal benefits of ML and AI usage in organizations because of their DC. This study was also one of the first empirical investigations that addressed the automation-augmentation paradox at the enterprise level.

This research study aims to inquire into the technostress phenomenon at an organizational level from machine learning (ML) and artificial intelligence (AI) deployment. The authors investigated the role of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management amongst managers.

The authors applied an exploratory qualitative method and conducted in-depth interviews based on a semi-structured interview questionnaire. Data were collected from 26 subject matter experts. The data transcripts were analyzed using thematic content analysis.

The study results indicated that role ambiguity, job insecurity and the technology environment contributed to technostress because of ML and AI technologies deployment. Complexity, uncertainty, reliability and usefulness were primary technology environment-related stress. The novel integration of ML and AI automation-augmentation interdependence, along with socio-technical systems, could be effectively used for technostress management at the organizational level.

This research study contributed to theoretical discourse regarding the technostress in organizations because of increased ML and AI technologies deployment. This study identified the main techno stressors and contributed critical and novel insights regarding the theorization of coping mechanisms for technostress management in organizations from ML and AI deployment.

The phenomenon of technostress because of ML and AI technologies could have restricting effects on organizational performance. Executives could follow the simultaneous deployment of ML and AI technologies-based automation-augmentation strategy along with socio-technical measures to cope with technostress. Managers could support the technical up-skilling of employees, the realization of ML and AI value, the implementation of technology-driven change management and strategic planning of ML and AI technologies deployment.

This research study was among the first few studies providing critical insights regarding the technostress at the organizational level because of ML and AI deployment. This research study integrated the novel theoretical paradigm of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management.

Social health insurance framework of any country is the national identifier of the country’s policy for taking care of its population which cannot access or afford quality healthcare. The purpose of this paper is to highlight the strategic imperatives of digital technology for the inclusive social health models for the BoP customers.

A qualitative exploratory study using in-depth personal interviews with 53 Indian health insurance CXOs was conducted with a semi-structured questionnaire. Using MaxQDA software, the interview transcripts were analyzed by means of thematic content analysis technique and patterns identified based on the expert opinions.

A framework for the strategic imperatives of digital technology in social health insurance emerged from the study highlighting three key themes for technology implementation in the social health insurance sector – analytics for risk management, cost optimization for operations and enhancement of customer experience. The study results provide key insights about how insurers can enhance the coverage of BoP population by leveraging technology.

The framework would help health insurers and policymakers to select strategic choices related to technology that would enable creation of inclusive health insurance models for BoP customers.

The absence of specific studies highlighting the strategic digital imperatives in social health insurance creates a unique value proposition for this framework which can help health insurers in developing a convergence in their risk management and customer delight objectives and assist the government in the formulation of a sustainable social health insurance framework.

Academic dialogue related to ‘organizational performance’ in strategic management has primarily centred around the industrial organization theory (IO) and resource-based view (RBV). Both perspectives, though conceptually dialectic, have served as primary competing theories governing research studies in the domain of strategic management. However, the confluence of these theoretical perspectives has not been adequately explored to advance a shared view of competitive advantage. This study aims to explore the likelihood of embedded commonalities between RBV and IO.

A bibliometric analysis was conducted to visualize the intellectual map of studies and knowledge development encompassing these theories. This was followed by a comprehensive literature review to understand how the business environment (BE) and organizational capabilities have contributed towards attaining competitive advantage.

This study established that connecting the intellectual boundaries of these theoretical perspectives would facilitate better comprehension of the processes and outcomes in organizations. Integrating the knowledge emerging out of this methodological blend, a convergence framework connecting the intellectual boundaries of both theories was presented.

The framework that emerged from this study would help in better understanding of organizational behaviour from a dual theoretical lens. It would also motivate future studies to consider RBV and IO as complementary theories rather than the current narrative of competing theories.

This study added to the efforts to achieve equilibrium between the BE and internal capabilities of organizations so as to maximize positive social externalities.

This study contributed to the limited attempts to leverage shared knowledge from a dual perspective using a comprehensive literature review in sequential combination with bibliometric analysis.

This study aims to explore the impact of the adoption of wearable technology products for Indian health insurance firms. It identifies the key dynamic capabilities that health insurance firms should build to manage big data generated by wearable technology so as to attain a competitive advantage.

A qualitative exploratory study using in-depth personal interviews with 53 Indian health insurance experts was conducted with a semi-structured questionnaire. The data were coded using holistic and pattern codes and then analyzed using the content analysis technique. The findings were based on the thematic and relational intensity analysis of the codes.

An empirical model was established where all the propositions were strongly established except for the moderate relationship between wearable technology adoption and product innovation. The study established the nature of the interaction of variables on technology policy, organizational culture, strategic philosophy, product innovation, knowledge management and customer service quality with wearable technology adoption and also ascertained its influence on firm performance and competitive advantage.

From a dynamic capabilities perspective, this study deliberates on wearable technology adoption in the health insurance context. It also explicates the relationship between the variables on technology policy, organizational culture, strategic philosophy, product innovation, knowledge management and customer service quality with wearable technology adoption on firm performance.

This study is one of the first studies to add the context of wearable technology and health insurance to the existing body of knowledge on dynamic capabilities and sustainable competitive advantage for the service sector. It would help existing and prospective players in adopting or setting up appropriate business models.

The purpose of this paper is to develop material for classroom teaching in the subject area of general management with retail industry focus.

The approach is a case study approach with an emphasis on building relevant issues for class discussions and providing opportunities for students to analyse using additional resources from the library, company web site and news paper articles.

The case research enabled us to understand the challenges faced by organised retail companies in Indian subcontinent with reference to logistics and sourcing. Organised retail is an emerging industry in India and it provides an interesting analysis for growth and entrepreneurial ventures. The case research also provided important insights into growth of retail industry, extent of consolidation happening within the industry due to the unorganised retail industry players aligning themselves as out sourcing partners for major retailers, etc. To this extent, there is scope for further research in this area of research.

There are issues related to ethical practices in sourcing. This issue did not probe into this aspect of the retail industry.

This case is originally developed by conducting interviews with company officials and collecting information using qualitative approach. The details provided are true to the timeline given in the case – 2011 in Indian setting – Mumbai.

This paper aims to present a new hybrid algorithm of Particle Swarm Optimization and the Genetic Algorithm (PSOGA) to optimize the space trusses with continuous design variables. The PSOGA is an efficient hybridized algorithm to solve optimization problems.

These algorithms have shown outstanding performance in solving optimization problems with continuous variables. The PSO conceptually models the social behavior of birds, in which individual birds exchange information about their position, velocity and fitness. The behavior of a flock is influencing the probability of migration to other regions with high fitness. The GAs procedure is based on the mechanism of natural selection. The present study uses mutation, random selection and reproduction to reach the best genetic algorithm by the operators of natural genetics. Thus, only identical chromosomes or particles can be converged.

In this research, using the idea of hybridization PSO and GA algorithms are hybridized and a new meta-heuristic algorithm is developed to minimize the space trusses with continuous design variables. To showing the efficiency and robustness of the new algorithm, several benchmark problems are solved and compared with other researchers.

The results indicate that the hybrid PSO algorithm improved in both exploration and exploitation. The PSO algorithm can be used to minimize the weight of structural problems under stress and displacement constraints.