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This study empirically aims to examine the relationship between Bangladesh’s pharmaceutical industry growth and macroeconomic indicators such as the inflation rate, gross domestic product (GDP) growth, foreign direct investment (FDI) inflows, exchange rate and export growth through the long- and short-run relationship.

Using the time series data from 1986 to 2020, this study was developed based on the autoregressive distributed lag (ARDL) framework for co-integration. In contrast, the Toda–Yamamoto Granger Causality approach was also used for finding the direction of causality.

This study used the ARDL bounds test, which found strong co-integration among the variables, indicating a long-term relationship between them. In the long run, inflation, exchange rate and export growth significantly positively influence the pharmaceutical industry’s growth. Surprisingly, an FDI inflow has a negative impact. In the short term, the exchange rate and GDP growth were found to influence the growth of the pharmaceutical industry positively. Bidirectional causality between the growth of the pharmaceutical industry and the exchange rate was also identified using the Granger causality approach.

This paper emphasizes developing the policy as well as making concrete decisions regarding the development of the pharmaceutical industry and economic development in Bangladesh. The results also highlight the necessity for strategic macroeconomic management to support this sector’s long-term development and global competitiveness.

To the best of the authors’ knowledge, this paper is conducted to identify the short- and long-run relationship of pharmaceutical industry development with the economic indicators and progress, where no study has been found on this dimension.

Purpose: The study aims to extract insights into five significant industries, pharmaceutical, space, defence, renewal energy, and information technology (IT), which have huge potential to make India achieving a five trillion-dollar economy in the future.

Design/methodology/approach: The authors focus on future-driven industries which are not only making India a third highest gross domestic product (GDP) producer country but also reviewing the different aspects of these industries and how they can assist India in achieving a five trillion-dollar economies along with determining India’s self-reliance through different governments initiatives in this direction.

Findings: The findings highlight the importance of inclusiveness of policymakers, stakeholders, private players, foreign investors, and the masses. Their significant contributions especially in the pharmaceutical, space, defence, renewal energy, and IT sectors in terms of creativities, innovations, intellect, executions, implementations, and improvements can assist India in achieving its five trillion-dollars economy soon.

Practical implications: This study offers (1) convincing insights into five key industries, pharmaceutical, space, defence, renewal energy, and IT, which have huge potential to increase total GDP volume shortly and (2) the investment areas for the masses where they can see their world not only self-reliant but also will see huge growth in their invested amount in these industries in future.

Originality/value: The insights of five key industries, pharmaceutical, space, defence, renewal energy, and IT, highlight that India has the potential to achieve a five trillion-dollar economy in the future; however, it does not ignore the significant contribution of other industries in making of total GDP.

The purpose of this paper is to investigate the impact of the COVID-19 pandemic on company innovation, specifically centering on the quantity and quality of innovation. The paper aims to provide a comprehensive understanding of whether the epidemic inhibits innovation and the role of digital transformation in mitigating this negative impact.

The paper uses a quasi-experimental study of the COVID-19 pandemic and constructs a differential model to analyze the relationship between the epidemic and firm innovation in three dimensions: total, quantity and quality. The paper also uses a difference-in-difference-in-differences model to test whether digital transformation of firms mitigates the negative impact of the epidemic and its mechanism of action.

The results show that COVID-19 significantly reduced the overall level of firm innovation, primarily in terms of quantity rather than quality. Furthermore, this study finds that digital transformation plays a pivotal role in mitigating the pandemic’s adverse impact on innovation. By addressing financing constraints and countering demand insufficiency, digital transformation acts as a catalyst for preserving and fostering innovation during and after the pandemic.

This study extends the current research on the pandemic’s impact on firm innovation at the micro level. It offers valuable insights into strategies for fostering digital transformation among Chinese enterprises in the post-pandemic era.

This paper aims to study the fluid flow and heat transfer within the Casson nanofluid confined between disk and cone both rotating with distinct velocities. For a comprehensive investigation, two distinct nano-size particles, namely, silicon dioxide and silicon carbide, are submerged in ethanol taken as the base fluid.

This paper explores the disk and cone contraption mostly encountered for viscosity measurement in various industrial applications such as lubrication industry, hydraulic brakes, pharmaceutical industry, petroleum and gas industry and chemical industry.

It is worth mentioning here that the radially varying temperature profile at the disk surface is taken into the account. The effect of prominent emerging parameters on velocity fields and temperature distribution are studied graphically, while bar graphs are drawn to examine the physical quantities of industrial interest such as surface drag force and heat transfer rate at disk and cone.

To the best of the authors’ knowledge, no study in literature exists that discusses the thermal enhancement of nano-fluidic transport confined between disk and cone both rotating with distinct angular velocities with heat transfer.

In recent years, technological advancement has played a crucial role in the growth of emerging economies. However, as with any novel technological development, there are often concerns and hesitations surrounding its implementation. This study aims to investigate the factors influencing blockchain adoption and usage. Thereby evaluating its impact on supply chain performance.

This is a deductive research based on the modified form unified theory of acceptance and use of technology, which is a persuasive model that has been used in numerous studies on the acceptance and usage of information technology systems. For this study, valid data was collected from 129 management-level supply chain professionals and policymakers working in diverse manufacturing industries. The collected data was used for testing hypotheses by deploying the structural equation modeling technique.

The findings of this study reveal that facilitating conditions and technology readiness highly are key influencers for organizations to implement this disruptive technology. Moreover, blockchain adoption and usage can significantly enhance supply chain performance.

Blockchain technology is a novel and promising disruptive technology that industries are looking forward to adopting and using. For the policymakers and supply chain strategists working in a developing country, this study offers a comprehensive viewpoint on the swift acceptance and usage of blockchain technology to facilitate supply chain operations.

Decision-making, reinforced by artificial intelligence (AI), is predicted to become potent tool within the domain of supply chain management. Considering the importance of this subject, the purpose of this study is to explore the triggers and technological inhibitors affecting the adoption of AI. This study also aims to identify three-dimensional triggers, notably those linked to environmental, social, and governance (ESG), as well as technological inhibitors.

Drawing upon a six-step systematic review following the preferred reporting items for systematic reviews and meta analysis (PRISMA) guidelines, a broad range of journal publications was recognized, with a thematic analysis under the lens of the ESG framework, offering a unique perspective on factors triggering and inhibiting AI adoption in the supply chain.

In the environmental dimension, triggers include product waste reduction and greenhouse gas emissions reduction, highlighting the potential of AI in promoting sustainability and environmental responsibility. In the social dimension, triggers encompass product security and quality, as well as social well-being, indicating how AI can contribute to ensuring safe and high-quality products and enhancing societal welfare. In the governance dimension, triggers involve agile and lean practices, cost reduction, sustainable supplier selection, circular economy initiatives, supply chain risk management, knowledge sharing and the synergy between supply and demand. The inhibitors in the technological category present challenges, encompassing the lack of regulations and rules, data security and privacy concerns, responsible and ethical AI considerations, performance and ethical assessment difficulties, poor data quality, group bias and the need to achieve synergy between AI and human decision-makers.

Despite the use of PRISMA guidelines to ensure a comprehensive search and screening process, it is possible that some relevant studies in other databases and industry reports may have been missed. In light of this, the selected studies may not have fully captured the diversity of triggers and technological inhibitors. The extraction of themes from the selected papers is subjective in nature and relies on the interpretation of researchers, which may introduce bias.

The research contributes to the field by conducting a comprehensive analysis of the diverse factors that trigger or inhibit AI adoption, providing valuable insights into their impact. By incorporating the ESG protocol, the study offers a holistic evaluation of the dimensions associated with AI adoption in the supply chain, presenting valuable implications for both industry professionals and researchers. The originality lies in its in-depth examination of the multifaceted aspects of AI adoption, making it a valuable resource for advancing knowledge in this area.

This study aims to (1) validate the efficacy of contractual and relational governance in enhancing operational performance and (2) explore the influence of product complexity on the effectiveness of these governance mechanisms, thereby determining the optimal approach for varying levels of product complexity.

By utilizing a comprehensive theoretical framework encompassing transaction cost economics, social exchange theory and contingency theory, this research explores the intricate interplay between governance mechanisms, product complexity and operational performance, drawing insights from a dataset comprising 246 responses within Mainland China’s manufacturing sector. To rigorously test the proposed hypotheses, this study employed a hierarchical regression analysis.

The findings of this study are summarized as follows: (1) while both contractual governance and relational governance have a significant impact on operational performance, relational governance is found to be more effective than contractual governance in enhancing operational performance; and (2) the moderation effect of product complexity is evident, as it weakens the impact of contractual governance while simultaneously enhancing the positive influence of relational governance on operational performance.

The study uncovers a moderation effect of product complexity on the relationship between governance mechanisms and operational performance. This finding adds an original contribution to the literature by highlighting how product complexity can interact with governance strategies, providing practical insights for industries dealing with varying levels of product complexity.

Although strategic scholars have made great effects to exploring the moderating roles of team interaction in explaining the effect of top management team (TMT) diversity, they have adopted seemingly conflicting theoretical perspectives to explain how it works. Drawing on ideas from the threat rigidity theory, the authors integrated these perspectives by proposing a contingency model in which the relationships between TMT diversity and adaptive firm performance depend on the matching between the internal context (i.e. overlapping team tenure) and external context (i.e. severity of threat).

This study sampled 579 Chinese A-share listed companies that have been severely affected by the COVID-19 pandemic, and multilevel linear regression analysis was used to test the hypothesis.

Results provided support for this hypothesis. Specifically, the interaction between TMT age/tenure diversity and overlapping team tenure is significant only when the severity of threat is high, while the interaction between TMT functional diversity and overlapping team tenure is significant only when the severity of threat is low.

The results of this study provide a comprehensive perspective to predict the performance impact of team diversity and contribute to diversity research and practice.

Service–sales ambidexterity (SSA) offers sales managers crucial information about dealing with customer service failures through an effective management control system. This study aims to scrutinize the relationships among SSA, salesforce control system, salesperson’s role stressors and service recovery performance (SRP) in the business-to-business (B2B) context.

An analysis is conducted based on survey data collected from 586 B2B sales employees participating in an extensive survey. Structural equation modeling is used to analyze the proposed hypotheses.

Empirical findings suggest that behavior-based control harms SSA. On the other hand, outcome-based control has a positive impact on SSA. The research outcomes further disclose that SSA positively impacts salesperson role conflict and emotional fatigue, whereas emotional fatigue negatively impacts SRP. Salesperson resilience notably moderates the association between SSA and emotional fatigue.

The study addresses there is a dearth of research on SSA applying the sales management control system. When studying about ambidexterity in sales context, many supervisory styles have been explored; however, to the best of the authors’ knowledge, this is the first systematic attempt to understand how sales management control systems play a role in SSA.

The purpose of the study was to examine the factors that are important for strengthening university–industry collaboration (UIC). This study also investigates the outcome of UIC in the light of creativity, skill, knowledge, and research work.

A survey method has been used to collect data for the study. This study applied a purposive judgmental sampling technique where particular types of respondents like university faculty members and the top officials of the organizations were selected who are knowledgeable and can provide the desired information. The current study used the structural equation modeling method to analyze the data. In the first stage, this research assessed the demographic factors of the respondent. Then this study conducts confirmatory factors analysis and convergent and discriminant validity and reliability test. Finally, the hypotheses are tested by using nonparametric.

This study finds that knowledge transfer mechanism, governmental factors, organizational design factors, technology transfer and the collaborative network has a significant impact on strengthening UIC, which ultimately facilitates creativity, knowledge creation, skills development and supply of graduate according to the requirement of the industry, good research work.

The current study identified some important determinant that has a substantial influence on strengthening UIC. According to the study organizational design, government, technology, collaborative network and mechanism for knowledge transfer play very crucial roles in strengthening collaboration that ultimately increases the creativity, skills, knowledge and research capability of graduates.