Md Rashed
59156818900
Publications - 10
Innovative configurations for organizational resilience: Bridging the proactive and reactive capability in volatile environments
Publication Name: Sustainable Futures
Publication Date: 2025-12-01
Volume: 10
Issue: Unknown
Page Range: Unknown
Description:
A growing concern among academics and professionals has placed organizational resilience (OR) at the leading edge of their studies' catalysts because of its peripheral vulnerability to turbulent environments in organizational settings. This research demonstrates the value of competitive advantage and the practices of resilient firms, thereby strengthening organizational resilience in a disruptive environment. Organizational resilience has been established as a process for gaining a competitive edge and enhancing firms' performance in a volatile environment where disruptions, such as epidemics, political turmoil, and economic instability, threaten the sustainability of their operations. Adopting the Dynamic Capability View (DCV), this study investigates proactive (PRO) and reactive (REA) capability configurations in relation to organizational resilience through partial least squares structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA). The study develops the measurement items for organizational resilience to test the proposed hypotheses using PLS-SEM and fsQCA. PLS-SEM finds that flexibility, collaboration, response, and recovery are positive drivers for organizational resilience, whereas fsQCA reveals that flexibility, response, and recovery are sufficient for the same outcome. The combined results indicate that flexibility, responsiveness, and recovery are key conditions for predicting high organizational resilience in a disruptive environment. The combined findings confirm that the measurement items of proactive and reactive performance significantly better align with organizational resilience and meet the "capability" and "resources" suitable criteria of DCV. The combined findings of this research make both theoretical and practical contributions to the foundation of pre-disruptive and post-disruptive resilience.
Open Access: Yes
Driving Social Entrepreneurship Among Students: Investigating Through PLS-SEM and fsQCA Approaches in Emerging Economies
Publication Name: Emerging Science Journal
Publication Date: 2025-06-01
Volume: 9
Issue: 3
Page Range: 1591-1609
Description:
This study aims to identify the relationship between social self-efficacy, social innovation, resilience, and proactive personality concerning university students’ behavioral intention to engage in social entrepreneurship, particularly in emerging economies, like Bangladesh. A structured questionnaire was utilized to collect quantitative data from 540 students in various disciplines of study as part of the study's quantitative research methodology using partial least squares-Structural Equation Modelling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). The analysis reveals that proactive personality traits are associated with the social entrepreneurship intention (SEI) and that leadership orientation is also significant to SEI. The study also demonstrates that social entrepreneurial activities tend toward higher social self-efficacy and resilience, making it crucial to focus on such characteristics while facing social risk and bearing innovations. This study's novelty lies in its focus on the unique combination of psychological traits—social self-efficacy, social innovation, resilience, and proactive personality—and their impact on university students' intention to engage in social entrepreneurship in emerging economies. Additionally, the research emphasizes the importance of integrating leadership skills and social innovation into academic curricula and policy development to foster social entrepreneurship. Practical implications indicate that leadership skills and social innovation should be included in the curricula of educational institutions, and supportive policies should be developed to create available resources for prospective social entrepreneurs.
Open Access: Yes
The influence of hybrid leadership in sustainable women entrepreneurial performance
Publication Name: Sustainable Futures
Publication Date: 2025-06-01
Volume: 9
Issue: Unknown
Page Range: Unknown
Description:
In the contemporary era, strategic leadership style plays significant role in entrepreneurial performance. The key purpose of this study is to examine the influence of hybrid (self, shared and opinion) leadership in women entrepreneurial performance towards sustainable growth. This mixed method study investigated data in two ways. First, the study analyzed the data and measured the hypotheses employing the partial least squares structured equation model (PLS-SEM) in SmartPLS software 4 packages. Second, fsQCA explores multiple causal relationships between the constructs. The fsQCA results claim that the multiple causal relationships among the shared, self and opinion leadership have strong significant impact on women entrepreneurial performance. In particular, it is addressed that different entrepreneurial performances are positively associated with the extent of self, shared and opinion leadership. Theoretically, this study contributes to the understanding of women leadership behavior in entrepreneurial performance with a mixed statistical analysis. The study has valuable insights for the women entrepreneurs and concerned
Open Access: Yes
Building organizational resilience in emerging economies: Strategic insights from Bangladesh
Publication Name: Sustainable Futures
Publication Date: 2025-12-01
Volume: 10
Issue: Unknown
Page Range: Unknown
Description:
Organizational resilience is a key aspect for sustaining comparative benefit and performance amidst uncertainties such as pandemics, political volatility, and financial crises. Despite its significance, limited studies have explored the potential sufficient solutions to resilience-enabling constructs, especially in emerging economies. This research combines the Resource-Based View (RBV) and Transaction Cost Economics (TCE) to propose a theoretical framework for understanding and predicting organizational resilience. Using survey data from 348 respondents serving corporate industries in Bangladesh, we employ Necessary Condition Analysis (NCA) and fuzzy set Qualitative Comparative Analysis (fsQCA) to identify causal configurations to predict organizational resilience. The findings reveal five configurations that are sufficient for achieving high resilience and four configurations associated with low resilience, highlighting the nuanced interplay between resources, costs, and adaptability. Specifically, flexibility, response, recovery, benevolence, and commitment must need conditions for achieving organizational resilience in NCA analysis. In fsQCA analysis, flexibility and commitment are core conditions, whereas response and information sharing are peripheral conditions for achieving high organizational resilience. This study strengthens resilient strategies by demonstrating the supplementary contributions of RBV and TCE. This combination offers policymakers actionable insights to develop resilient strategies that enhance organizational adaptability and performance in turbulent times.
Open Access: Yes
Strategizing for Sustainability: Examining the Dynamic Interplay of the Circular Economy, Green Technology Innovation, and Green Performance
Publication Name: Global Journal of Flexible Systems Management
Publication Date: 2025-12-01
Volume: 26
Issue: 4
Page Range: 935-961
Description:
Environmental challenges critically affect manufacturing firms which face numerous concerns regarding their sustainable operations. These operations aim to operationalize the dimensions of circular economy capabilities (CEC) and green technology innovation (GTI) to strengthen competitiveness in fragile environments. This research validates a holistic understanding of green performance by integrating theories and dimensions to identify effects that predict sustainable green performance. Drawing from the green dynamic capability view (GDCV), which is a contextual extension of the DCV and flexible systems management (FSM) paradigm, this study investigates how CEC and GTI predict green performance (GP). Survey data of 301 senior professionals from manufacturing firms acquired from a developing country, such as Bangladesh, were used. To assess the survey data, the study used a multimethodological approach using Necessary Condition Analysis (NCA) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to investigate the suggested tie in the midst of the CEC and GTI on the GP. The findings reveal that all the antecedents of the circular economy are necessary conditions except absorptive capacity to predict green performance, as reported in the NCA. The fsQCA results show that combinations of CEC and GTI are sufficient conditions to predict high green performance. This research uses a unique combination of CEC and GTI to predict high GP via the supplementary method of fsQCA. Therefore, the findings should also motivate professionals of manufacturing firms to focus even more on the necessity effects of a single condition to predict GP and the asymmetric effects of combinations of CEC and GTI to produce multiple configurations to predict high green performance.
Open Access: Yes
Sustainability catalysts and green growth: Triangulating evidence from EU countries using panel data, MMQR, and CCEMG
Publication Name: Green Technologies and Sustainability
Publication Date: 2026-04-01
Volume: 4
Issue: 2
Page Range: Unknown
Description:
Green Growth Strategies (GGS) are a win–win opportunity for not only the nation’s economy but also the environment. However, many countries are not concerned about reaping these benefits, and they continue to harm the environment for short-term gain, neglecting long-term sustainability. Southern European countries can utilize green growth policies to enhance their competitiveness, bypass older, more polluting technologies by directly adopting cleaner alternatives, and achieve economic and environmental progress. To address this concern, we analyzed 12 Southern European countries from 2010 to 2019, investigating how they can enhance their green growth performance by incorporating critical predictors. We employed panel data estimators, mean group (MG) to accommodate slope heterogeneity, and Common Correlated Effects Mean Group (CCEMG), which opens the opportunity to observe the influence of unobserved common factors and allows us to capture cross-sectional dependence and heterogeneous behavior better. We applied the Method of Moment Quantile Regression (MMQR) technique further as a robustness check to capture heterogeneous effects across the green growth distribution. The same methodology with ecological footprint data and implementation of the Generalized Method of Moments (GMM) has eliminated the endogeneity concern. The findings highlighted that educational attainment, globalization, and renewable energy consumption have positive influences on green growth. In comparison, trade openness and natural resource rent exhibit negative effects when we shift the methodology from MG to CCEMG, giving us a total of four significant factors to be concerned with. The study emphasizes the crucial importance of tailored policy approaches and regional collaboration in addressing environmental challenges effectively, and offers actionable insights for achieving green growth in the region by providing empirically grounded and practical recommendations that account for diverse socioeconomic contexts and ecological vulnerabilities.
Open Access: Yes
Dynamic Capabilities and Technological Innovation for Firm Resilience: A Configurational Analysis
Publication Name: Emerging Science Journal
Publication Date: 2025-10-01
Volume: 9
Issue: 5
Page Range: 2292-2317
Description:
Firm resilience is essential to manage response and rapid recovery from disruptive events for a firm. Moreover, there is limited literature that investigates the combined effects of dynamic capability and technological innovation that are interrelated with firm resilience. This study used the dimensions of firm resilience, which were investigated with both necessary condition analysis (NCA) and fuzzy-set Qualitative Comparative Analysis (fsQCA) methods using survey questionnaires from 308 respondents operating in Bangladeshi corporate industries that are currently facing uncertainties due to unforeseen crises. NCA results showed that visibility, market position, and digitalization achieved firm resilience as these antecedents reached the full percentile to achieve an optimal level of outcome. On the contrary, the influence of reserve capacity and big data analytics was not empirically significant for achieving firm resilience. Moreover, fsQCA results appreciated NCA results and showed four solutions that are sufficient for achieving a high level of firm resilience. The study reveals the configurational effects of dynamic capabilities and technological innovation to achieve firm resilience. The results show the necessary effects of configurational relationships that lead to outcomes. The configurational method is applied to identify the combined effects of antecedents that help managers predict high levels of firm resilience in a turbulent environment.
Open Access: Yes
Configuring Green Growth in the Age of Sustainability: Energy and Resource Use Trends in EU Economies
Publication Name: Sustainable Development
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
In an era of intensifying global competition where nations aggressively pursue economic advancement, the imperative to balance progress with ecological preservation has become paramount. However, the race for advancement should not harm nature or future generations. Our study investigates the drivers that can lead to green growth, aligning with sustainable development principles that integrate economic growth, environmental stewardship, and social equity as per the UN's Sustainable Development Goals (SDGs), across nine Western European countries from 2010 to 2019. By utilizing panel data from reputable sources, this research investigates the influence of globalization, natural resource rents, renewable energy consumption, trade openness, and total energy consumption on green growth. Employing contemporary panel diagnostic tests, cointegration analyses, and fixed- and random-effects models, the study also validates its findings through quantile regression, fully modified ordinary least squares, and dynamic ordinary least squares. Our study has fulfilled its destiny by finding the right drivers. According to various analyses, globalization and trade openness consistently and significantly promote green growth, confirming their potential as reliable mechanisms for achieving green growth. The complex impact of renewable energy consumption and natural resource rents opens a new door for exploration by revealing the transitional barriers, such as initial costs and policy lags, in contrast to maintaining the resource rent tendency. However, the beneficial impact of total energy consumption of carbon and fossil fuel underscores the urgency of effective resource utilization and a shift toward renewable sources to decouple growth from unsustainable consumption before running out.
Open Access: Yes
DOI: 10.1002/sd.70627
Drivers of E-Tourism Adoption in Bangladesh: An Extended UTAUT Model Integrating Digital Literacy and Vacation Packages
Publication Name: Ianna Journal of Interdisciplinary Studies
Publication Date: 2026-01-05
Volume: 8
Issue: 1
Page Range: 814-829
Description:
Background: The adoption of technology in the tourism industry has become a worldwide trend aimed at enhancing effectiveness and efficiency in this sector. Objectives: This study investigates the drivers influencing e-tourism adoption in Bangladesh by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) model with the addition of digital literacy and vacation packages. Methodology: This research proposes and tests a conceptual model grounded in complexity and configuration theory. We employ a mixed-method analytical approach, integrating Fuzzy-Set Qualitative Comparative Analysis (fsQCA) as a complementary tool to Structural Equation Modelling (SEM). Empirical validation was conducted using data from 297 online tourists. Results: Structural Equation Modelling (SEM) revealed that e-tourism adoption intention was significantly influenced by vacation packages, effort expectancy, performance expectancy, facilitating conditions, and digital literacy, whereas social influence did not show a significant effect. Furthermore, Fuzzy-Set Qualitative Comparative Analysis (fsQCA) identified five sufficient configurations of these causal conditions that lead to high levels of e-tourism adoption. Conclusion: The findings confirm the primary drivers of e-tourism adoption in Bangladesh and identify five specific, high-adoption pathways. Practically, these results enable e-tourism service providers and policymakers to strategically allocate resources, optimise platform design, and implement targeted digital literacy initiatives to accelerate e-tourism adoption rates in the region. Unique Contribution: This research provides a significant methodological advancement by integrating SEM and fsQCA to move beyond testing net effects and establish a detailed, configurational understanding of e-tourism adoption. Theoretically, it extends the UTAUT model by identifying new context-specific causal conditions relevant to travellers in Bangladesh. Key Recommendation: It is suggested that online travel service providers, marketers, and digital platform executives utilise the detailed findings of this study. Specifically, they should consider developing and implementing strategies that focus on optimising the five sufficient causal configurations identified by fsQCA and prioritise investments in the factors (e.g., performance expectancy, digital literacy) that significantly influence e-tourism adoption among Bangladeshi travellers.
Open Access: Yes
Innovation Pathways to Carbon Efficiency: Disentangling the Effects of AI, R&D, and Clean Energy Blessings on U.S. Environmental Sustainability
Publication Name: Business Strategy and the Environment
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
The United States (U.S.) faces challenges in achieving its ambitious net-zero carbon emissions target by 2050, with current emissions having fallen by less than 1% in 2024. Despite an investment of $500 billion in low-carbon resources while holding the second-largest green technology patent portfolio globally, it is further imperative to investigate ongoing innovations for suboptimal resource allocation and policy misalignment between investment strategies and environmental effectiveness. In this study, we examine the comparative impacts of artificial intelligence (AI) innovation, research and development (R&D) investment, government intervention, natural resource rents, and renewable energy consumption on U.S. environmental sustainability (ECOI) spanning 1990–2022. We bridge the gap in prior literature with respect to understanding which pathways of innovation lead to the highest carbon efficiency returns per dollar invested, moving beyond aggregate investment analysis toward identifying the optimal policy sequencing and resource allocation strategies. We implemented a comprehensive time series econometric framework, including autoregressive distributed lag bounds testing, the vector error correction model, and Granger causality analysis on 33 years of national-level data. Our findings suggest that R&D investment results in the greatest improvement in long-term carbon intensity, followed by AI patents and renewable energy usage. Government intervention has significant negative long-term effects despite positive short-term impacts, which may indicate potential crowding-out effects. Natural resource dependency has positive long-term benefits with negative short-term impacts, suggesting opportunities for strategic extraction. The error correction mechanism implies a moderate adjustment speed toward equilibrium, whereas impulse response functions (IRFs) reveal that AI innovations establish rapid environmental benefits peaking in the second period. These results provide crucial evidence for federal climate investment prioritization by suggesting that taking funds away from direct government spending and putting them into AI-integrated R&D initiatives could maximize carbon reduction outcomes and accelerate progress toward net-zero targets.
Open Access: Yes
DOI: 10.1002/bse.70748
