Environmental Challenges 14 (2024) 100832 Contents lists available at ScienceDirect Environmental Challenges journal homepage: www.elsevier.com/locate/envc Unveiling the link between environmental management accounting, energy efficiency, and accountability in state-owned enterprises: An integrated analysis using PLS-SEM and fsQCA Md. Mominur Rahman a, *, Shuvabrata Saha b, Mahfuzul Hoque c a b c Major in Accounting and Information Systems, Research Wing, Bangladesh Institute of Governance and Management, Dhaka 1207, Bangladesh Department of Accounting and Information Systems, Comilla University, Cumilla 3506, Bangladesh Department of Accounting and Information Systems, Dhaka University, Dhaka, Bangladesh A R T I C L E I N F O A B S T R A C T Keywords: Environmental management accounting Energy efficiency Accountability Transparency Responsibility Answerability The rising importance of sustainability and accountability in organizations has prompted the exploration of innovative approaches to enhance environmental performance and energy efficiency (ENE). The purpose of this research is to examine the extent to which environmental management accounting (EMA) and ENE practices contribute to accountability within state-owned enterprises (SOEs) in Bangladesh. This study employs both symmetrical (PLS-SEM) and asymmetrical (fsQCA) approaches. The study verifies internal consistency, reli­ ability, validity, common method bias, and collinearity issues through measurement model analysis and conducts path analysis after testing model fitness in structural model analysis. Finally, the study uses fsQCA to conduct indepth analyses of causal contributions from different conditions to a specific outcome of interest. The PLS-SEM analysis revealed significant positive relationships between EMA and ENE with transparency, responsibility, and answerability. These results indicate that organizations adopting EMA and ENE practices are more likely to exhibit higher levels of transparency, demonstrate greater responsibility towards environmental matters, and be more answerable to stakeholders for their accountability. Further, the study identified ENE as a mediator of EMA and accountability. Finally, the fsQCA analysis supported the importance of both EMA and ENE as necessary conditions for achieving accountability indicating the integration of EMA and ENE to foster transparency, re­ sponsibility, and answerability effectively. This study implies that by implementing EMA systems and focusing on energy-efficient operations, organizations can enhance transparency, responsibility, and answerability to stakeholders, fostering a positive image and reputation. Therefore, SOEs may consider integrating these practices into their overall sustainability strategies to maximize their impact on accountability and environmental performance. 1. Introduction In recent years, there has been a growing global concern about environmental sustainability and the need for businesses to adopt more responsible practices (Greiling et al., 2015; Jiao et al., 2023; Kaur and Lodhia, 2019; Murshed et al., 2022; Rahman and Halim, 2022). State-owned enterprises (SOEs) in Bangladesh, as in many other coun­ tries, play a significant role in the national economy. As major players in various industries, their operations can have a considerable impact on the environment. It has become crucial for these SOEs to address envi­ ronmental issues and be held accountable for their actions, not only to comply with regulations but also to contribute to the overall sustainable development goals of the country (Burritt et al., 2019). Environmental Management Accounting (EMA) has emerged as a potential tool for organizations to integrate environmental considerations into their decision-making processes and financial management. EMA involves identifying, analyzing, and reporting environmental costs and benefits, which can help companies improve resource efficiency and environ­ mental performance (Deb et al., 2022). By implementing EMA practices, SOEs in Bangladesh could gain better insights into their environmental impacts, identify areas for improvement, and enhance their account­ ability for environmental outcomes. Moreover, energy efficiency is a critical aspect of environmental sustainability (Christensen and Himme, 2017; Kumalawati et al., 2023; * Corresponding author. E-mail address: mominurcou@gmail.com (Md.M. Rahman). https://doi.org/10.1016/j.envc.2023.100832 Received 30 November 2023; Received in revised form 17 December 2023; Accepted 27 December 2023 Available online 30 December 2023 2667-0100/© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Md.M. Rahman et al. Environmental Challenges 14 (2024) 100832 This study makes a significant contribution in at least four key ways. Firstly, it addresses a crucial knowledge gap by investigating the influ­ ence of EMA and energy efficiency on accountability, a relationship that has been underexplored in previous research. Thus, this investigation provides valuable insights into the literature on sustainability and accountability. Secondly, the study contributes to filling a contextual gap as prior research concentrated on Western contexts, leaving emerging economies like SOEs in Bangladesh. Thus, this unique context offers valuable implications for organizations operating in similar en­ vironments where environmental sustainability and accountability are gaining importance. Thirdly, the study methodologically contributes to combining symmetrical (PLS-SEM) and asymmetrical (fsQCA) ap­ proaches to analyze a more comprehensive and nuanced understanding of the relationships between EMA, ENE, and accountability. Finally, this study contributes to identifying energy efficiency as a mediator of EMA and accountability in SOEs that provides valuable guidance to practi­ tioners and policymakers seeking to enhance sustainability and accountability in organizations. Uddin et al., 2023). Improving energy efficiency not only reduces greenhouse gas emissions but also results in cost savings and enhances operational efficiency for companies. In the context of SOEs in Bangladesh, implementing energy-efficient measures can significantly contribute to reducing their carbon footprint and aligning with national and international commitments for environmental conservation. Addi­ tionally, accountability is a key aspect of responsible business practices. In the context of environmental issues, accountability can be examined through three dimensions: transparency, responsibility, and answer­ ability (Ball et al., 2014). Transparency involves disclosing information and processes related to environmental performance and decision-making. Responsibility refers to accepting and acting upon the consequences of environmental impacts and decisions. Answerability refers to being answerable to stakeholders for actions taken concerning the environment. In the context of environmental management, accountability holds paramount importance as it ensures that organi­ zations take responsibility for their environmental impact and adhere to sustainable practices. Accountability involves transparency in disclosing environmental performance, taking responsibility for environmental outcomes, and being answerable to stakeholders for environmental de­ cisions (Bebbington et al., 2014; Burritt and Welch, 1997; Chang and Deegan, 2008). The research gap in the context of the study lies in the limited exploration of the relationship between EMA, energy efficiency, and accountability (transparency, responsibility, and answerability) within SOEs in emerging economies like Bangladesh. While some studies have separately investigated the impact of EMA and ENE on environmental performance, there is a notable absence of comprehensive research that examines how these practices jointly contribute to accountability di­ mensions in the specific context of SOEs. Several prior studies have focused on EMA’s influence on environmental performance (Jiao et al., 2023), while others have explored the impact of ENE on carbon pro­ ductivity and energy sustainability (Murshed et al., 2022; Rahman and Islam, 2023; Zhang et al., 2021), and others focused on sustainable development (Halim and Rahman, 2022; Md Mominur Rahman, 2023; Rahman et al., 2023). However, there is a lack of research that delves into the integrated effects of both EMA and ENE on accountability di­ mensions such as transparency, responsibility, and answerability in SOEs. Moreover, while some studies have analyzed the mediating role of energy efficiency in the relationship between green accounting and environmental performance (Rahman and Islam, 2023), and between sharing economy benefits and sustainable development goals (Chien, 2022), there is limited research exploring the mediating role of energy efficiency in the relationship between EMA and accountability in SOEs. The role of energy efficiency in linking EMA practices with account­ ability dimensions in this specific organizational context remains largely unexplored. Furthermore, most of the existing research on EMA and ENE has predominantly focused on private corporations and Western con­ texts (Kumalawati et al., 2023; Qian et al., 2021). The dearth of studies in the context of SOEs in emerging economies like Bangladesh creates a research gap that needs to be addressed. This study aims to examine the extent to which EMA and ENE practices contribute to accountability (transparency, responsibility, and answerability) within SOEs in Bangladesh. The study seeks to address a significant research gap by examining how these environmental man­ agement and energy efficiency practices jointly influence account­ ability, a relationship that has not been explored in prior research. The following are the research questions: 2. Literature review 2.1. Environmental management accounting (EMA) and accountability EMA has emerged as a crucial tool for organizations to address sus­ tainability concerns and enhance their environmental accountability. Agyemang et al. (2021) used a machine learning approach to track the evolution of EMA research, revealing a recent focus on topics like corporate social responsibility and stakeholder theory within accounting journals. Conversely, studies outside accounting journals have delved into more specific areas, such as the shift to a low-carbon or circular economy and the attainment of sustainable development goals (SDGs). Additionally, new methodologies, like accounting for ecosystem ser­ vices, have garnered attention (Amoako et al., 2021). Andrew (2000) explored the transformative potential of environmental accountability, emphasizing the importance of integrating environmental issues into accounting practice. Moreover, Bartelmus (2008) pointed out that while corporations increasingly adopt environmental management as part of corporate social responsibility, they may be less inclined to publicly account for their environmental impacts, especially in monetary terms. Despite this, there is a growing interest in sustainability accounting and accountability in the public sector, as it holds vast potential for advancing the sustainability agenda (Ball et al., 2014). Baudot et al. (2020) examine how corporate tax behavior impacts reputation as a corporate social responsibility issue, finding no clear trend indicating that reputation is associated with specific types of tax behaviors. Bebbington et al. (2014) emphasize the fundamental role of sustainability accounting and accountability in pursuing low-carbon and sustainable societies, discussing various topics such as management accounting, sustainability reporting, and the role of accounting in addressing key sustainability issues like climate and human rights. Benston (1982) delves into social responsibility accounting, demon­ strating its potential to measure and control externalities resulting from corporate actions. Burritt et al. (2019) explore the diffusion of EMA innovations in businesses across Indonesia, the Philippines, and Viet­ nam, highlighting the importance of incremental changes and interdis­ ciplinary execution to foster cleaner production practices. Chang and Deegan (2008) focus on the relationship between EMA and cleaner production within universities, identifying three strategies through which cleaner production can benefit businesses: efficiency, consis­ tency, and sufficiency. They emphasize the need to understand the in­ formation requirements for each strategy and explore the potential role of EMA in meeting those needs. Cordonier Segger (2003) emphasizes the need for integrated envi­ ronmental, social, and economic progress to achieve sustainable devel­ opment, with a focus on the private sector’s role in addressing global challenges such as climate change, resource depletion, and social issues. 1. Does EMA affect the accountability of SOEs in Bangladesh? 2. Does energy efficiency affect the accountability of SOEs in Bangladesh? 3. Does energy efficiency mediate the link between EMA and the accountability of SOEs in Bangladesh? 2 Md.M. Rahman et al. Environmental Challenges 14 (2024) 100832 Du Rietz (2018) challenges traditional views of knowledge and infor­ mation in accountability settings, introducing the "knowing-in-practice" perspective to understand how information contributes to knowledge in demanding accountability, particularly in addressing environmental, social, and governance issues. Greiling et al. (2015) examine the adop­ tion of sustainability reporting guidelines by public sector organizations in Austria, Germany, and Switzerland, highlighting variations in compliance and information imbalances concerning economic, envi­ ronmental, and social aspects of sustainable development. Gunarathne et al. (2023) adopt a contingency theory perspective to explore the integration challenges between environmental strategy and EMA, finding that organizations at different stages of environmental man­ agement maturity show varying EMA implementation, suggesting that as firms progress towards proactive environmental strategies, EMA evolves to encompass more sophisticated environmental management activities. Furthermore, Hana and Astuti (2023) investigate the impact of implementing green accounting and CSR on the profitability of manufacturing companies listed on the Indonesia Stock Exchange, finding no significant effect on profitability. The study highlights the need for complete and accurate environmental information and disclo­ sure of CSR activities to promote sustainable practices in manufacturing companies. Hossain et al. (2020) investigated the effects of green banking practices on the financial performance of listed banking companies in Bangladesh. The study found a positive relationship between green banking practices and financial performance, suggesting that initiatives like green finance and green cost management could contribute to both environmental and economic performance. Kaur and Lodhia (2019) provided an overview of sustainability accounting, accountability, and reporting in the public sector. Larrinaga-Gonzélez and Perez-Chamorro (2008) analyzed how Spanish public water companies communicated sustainability information to stakeholders and explored the potential for more progressive accountability in the public sector compared to private sector organizations. Lehman and Morton (2017) delved into the rela­ tionship between corruption, social and environmental accounting, and civil society frameworks. Liu and Bai (2022) studied the impact of ownership structure and environmental supervision on the environ­ mental accounting information disclosure quality of high-polluting en­ terprises in China. The findings revealed complex relationships between ownership structure, environmental supervision, and environmental accounting information disclosure. Margerison et al. (2019) explored the prospects for environmental accounting and accountability in China, suggesting a shift towards an ecological civilization and an emerging interest in ancient Chinese philosophy among Chinese accountants. Marrone et al. (2020) used a machine learning method to track research trends in environmental accounting, both within and outside accounting journals, revealing a focus on topics like corporate social responsibility and sustainability goals. McLaren (2004) argued that corporate social and environmental abuses stem from a lack of accountability and proposed socially responsible investor engagement as a means to protect stakeholder in­ terests. Qian et al. (2011) examined the motivations for adopting EMA in local government waste management, finding both social structural and organizational contextual influences. Ribeiro and da Silva Monteiro (2019) filled the gap in research on social and environmental accounting in the Portuguese public sector, highlighting the role of accountants in encouraging sustainability accounting practices. Schaltegger (2018) discussed the links and potential connections between EMA and global ecological issues of sustainability. Sukoharsono (2007) emphasized the importance of green accounting in Indonesia for organizational accountability and its relevance in decision-making. Yusoff and Darus (2012) investigated environmental reporting practices in Malaysian public listed companies as a mechanism for corporate accountability and stakeholder engagement. Zadek et al. (2013) addressed the growing practice of social and ethical accounting, auditing, and reporting, examining its implications for corporate responsibility. Finally, Zyznarska-Dworczak (2019) explored the impact of accountability on accounting development, emphasizing sustainability accounting as a manifestation of corporate responsibility aligned with the concept of sustainability. Together, these studies shed light on the evolving land­ scape of environmental accounting, corporate accountability, and sus­ tainable practices in different regions and industries. The research on EMA and its relationship with accountability has not been investigated in the literature, as evidenced by the findings of numerous studies (Margerison et al., 2019; Marrone et al., 2020; Sukoharsono, 2007; Zyznarska-Dworczak, 2019). The existing body of literature has covered various aspects of EMA, including its imple­ mentation, effects on financial performance, reporting practices, and its role in sustainability and corporate responsibility (Lehman and Morton, 2017; Ribeiro and da Silva Monteiro, 2019; Zadek et al., 2013). How­ ever, while the literature provides valuable insights into accountability, there is a noticeable research gap concerning the specific mechanisms through which EMA enhances accountability. While some studies have touched upon the broader concept of accountability in the context of environmental and social issues (Cordonier Segger, 2003; Liu and Bai, 2022), they have not explicitly delved into the underlying dimensions or pathways through which EMA may influence accountability. As such, the following hypothesized (H1, H2, and H3) mechanisms of trans­ parency, responsibility, and answerability present potential avenues for investigating the specific ways in which EMA practices contribute to enhanced accountability in the SOEs. H1: EMA enhances accountability through transparency. H2: EMA enhances accountability through responsibility. H3: EMA enhances accountability through answerability. 2.2. Energy efficiency and accountability Ahern et al. (2018) reported on a study that examined how a building Control system of accountability could improve compliance and enhance building energy efficiency in new constructions. But Ahmed et al. (2022) investigated the effect of democracy, economic complexity, and renewable energy technology budgets on the ecological footprint in G7 countries and found that economic complexity reduced the ecolog­ ical footprint, but greater democratic accountability increased it, while renewable energy technology budgets mitigated the ecological foot­ print. In line with this, Burritt and Welch (1997) took an exploratory approach to develop an accountability framework and highlighted key stakeholders and dimensions of environmental accountability, recom­ mending ways to measure and enhance accountability for environ­ mental performance. Christensen (2016) investigated corporate accountability reporting and its potential in preventing high-profile misconduct. But Dutta (2016) explored corporate accountability for green growth and its relevance in addressing climate change challenges and environmental sustainability, and emphasized the importance of corporate social responsibility and green growth to tackle environ­ mental threats. Grant and Vasi (2017) explored how local environmental non-governmental organizations (NGOs) contribute to reducing carbon dioxide emissions from US power plants by disseminating environ­ mental norms and enhancing subnational climate policies. Hawrysz and Foltys (2015) examined the environmental aspects of social re­ sponsibility in public sector organizations, revealing that Polish entities lagged behind their foreign counterparts in developing internal envi­ ronmental responsibility. Lambin (2020) delved into global corporate accountability, emphasizing the need for societal corporate account­ ability systems to manage economic and societal responsibilities. Lev­ idow and Raman (2020) examined competing sociotechnical imaginaries of low-carbon waste-energy futures in the UK, highlighting how dominant techno-market fixes prioritize certain trajectories while marginalizing alternative eco-localization imaginaries. Lastly, Mäkelä and Cho (2022) discussed the responses of organizations to calls for 3 Md.M. Rahman et al. Environmental Challenges 14 (2024) 100832 accountability and sustainability, categorizing them from reac­ tive/symbolic to holistic approaches. Together, these studies shed light on the complexities of environmental accountability and corporate re­ sponses to sustainability challenges, showcasing the role of NGOs, public sector organizations, and societal calls in shaping corporate behavior and environmental outcomes. Mohammed (2013) proposes a conceptual framework integrating sustainability into corporate accountability, emphasizing the need for a meaningful and ethical approach to corporate value creation. Parmi­ giani et al. (2011) explore the performance implications of supply chain configuration and capabilities in response to the public’s increasing demand for social and environmental accountability from companies. Roberts et al. (2021) shed light on corporate accountability towards species protection, considering species as stakeholders and examining relationships between ecological consciousness and external assurance, environmental performance, and partnerships. Samuels (2005) dis­ cusses the global environmental malaise and emphasizes the importance of individual conscience and immediate precautionary measures to safeguard the environment for future generations. Sareen and Haarstad (2020) address the crisis of accountability in enabling equitable decar­ bonization, emphasizing the need to incorporate power imbalances and carbon emissions into sustainable energy governance. Sonetti and Cot­ tafava (2022) propose an energy cluster approach for universities’ en­ ergy profiles, enhancing comparability within sustainability rankings and considering building functions and characteristics. Sulkowski and Dobrowolski (2021) investigate the role of supreme audit institutions (SAIs) in energy accountability in EU countries, suggesting the need for SAIs to adopt a more substantial involvement in energy accountability at the supranational scale. Welke (2011) highlights the importance of en­ ergy efficiency and its accountability, urging individuals to moderate resource consumption and take responsibility for environmental quality. While a number of studies cover a wide range of topics related to sustainability, corporate accountability, and environmental re­ sponsibility, there is a lack of specific focus on the direct link between energy efficiency and these three dimensions of accountability (Mohammed, 2013; Parmigiani et al., 2011; Roberts et al., 2021; Sam­ uels, 2005; Sareen and Haarstad, 2020; Sonetti and Cottafava, 2022; Sulkowski and Dobrowolski, 2021; Welke, 2011). Although some studies touch upon the importance of accountability in the context of energy and environmental performance, none of them explicitly investigate the mechanisms through which energy efficiency contributes to enhancing transparency, responsibility, and answerability in organizations’ oper­ ations and decision-making processes. Therefore, there is a clear research gap that warrants further exploration and empirical investi­ gation to understand how energy efficiency initiatives can promote greater accountability by fostering transparency in reporting, encour­ aging a sense of responsibility towards environmental impact, and enabling organizations to answer for their actions and decisions in the realm of sustainable energy practices. Addressing this gap, the study postulates the following hypotheses. energy costs can lead to reduced environmental impact and improved corporate reputation. Deb et al. (2022) investigate the impact of EMA on the environmental and financial performance of manufacturing com­ panies in Bangladesh. Their study reveals a positive association between EMA and both environmental and financial performance, indicating that effective environmental accounting practices can lead to improved organizational outcomes. In a different context, Deb et al. (2020) explore the relationship between green accounting practices and bank performance in Bangladesh. Their research highlights the significance of green invest­ ment, green initiatives, and green activity management in influencing bank performance positively. Moreover, they find that better green ac­ counting practices correlate with higher bank performance, providing managerial implications for policymakers and corporations. Meanwhile, Gunarathne and Lee (2015) undertake a case study on a hotel in Sri Lanka to understand the development and implementation of EMA. The study reveals how the hotel’s selective EMA practices evolved into comprehensive ones, integrated into daily management processes with the support of all stakeholders. The increasing concern about environmental pollution and industrial waste has compelled manufacturing organizations to seek potential so­ lutions for achieving business sustainability and competitive advantage. In the context of developing countries, such as Bangladesh, Rahman and Islam (2023) discovered that green accounting positively influences environmental performance, and this relationship is partly mediated by energy efficiency. The study emphasized that integrating green ac­ counting practices can lead to better energy efficiency, thus promoting environmental sustainability and enhancing the reputation and competitive advantage of pharmaceutical and chemical companies. Furthermore, Rahman and Rahman (2020) explored the concept of green reporting as a tool for environmental sustainability. The study highlighted the significance of green reporting in accounting for envi­ ronmental costs and promoting corporate social responsibility. Green reporting was identified as an essential element for companies to miti­ gate pollution and efficiently utilize resources. Rahman et al. (2021) focused on the adoption of environmental management systems and environmental accounting practices in the context of emerging nations, including Bangladesh, and found that greater adoption of environmental management systems and effective environmental accounting practices positively impacted cost advantage, simultaneously protecting the environment and reducing costs for or­ ganizations. In the Portuguese context, Ribeiro et al. (2016) investigated the determinants of environmental accounting and reporting practices in local entities, and revealed that the degree of development of envi­ ronmental accounting and reporting practices was low in Portuguese local entities. While some studies emphasized the positive influence of EMA on business sustainability and competitive advantage (Jiao et al., 2023; Kumalawati et al., 2023), others explored its relationship with environmental performance (Rahman and Islam, 2023) and cost advantage (Rahman et al., 2021). Additionally, certain research high­ lighted the significance of green reporting and green intellectual capital in promoting environmental responsibility and sustainable practices (Rahman and Rahman, 2020; Ribeiro et al., 2016). However, a potential research gap can be observed in the specific investigation of the link between EMA and energy efficiency. Therefore, there is a need for research that delves into the relationship between EMA practices and energy efficiency to better comprehend the role of EMA in optimizing energy consumption. By addressing this research gap, this research of­ fers the following hypothesis. H4: Energy efficiency enhances accountability through transparency. H5: Energy efficiency enhances accountability through responsibility. H6: Energy efficiency enhances accountability through answerability. 2.3. Environmental management accounting and energy efficiency In recent years, there has been a growing recognition of the impor­ tance of accountability in various domains, including corporate, public sector, and environmental management. Bracci et al. (2015) delve into the implications of austerity policies on public sector accounting sys­ tems, highlighting the need for critical debates on how accounting is shaping constructions of austerity and the roles of public sector ac­ countants. Christensen and Himme (2017) propose a statistical approach to measure energy consumption effectively, aiming to enhance EMA practices. They emphasize that proper monitoring and control of H7: EMA enhances energy efficiency. 2.4. Mediating effects of energy efficiency While the studies by Rahman and Rahman (2020), Rahman and Islam (2023), Jiao et al. (2023), Kumalawati et al. (2023), Qian et al. 4 Md.M. Rahman et al. Environmental Challenges 14 (2024) 100832 (2021), Ribeiro et al. (2016), Chien (2022), Murshedet al. (2022), and Zhang et al. (2021) have provided valuable insights into the relationship between various environmental factors and energy efficiency, a notable research gap remains concerning the mediating role of energy efficiency in the context of EMA and its impact on transparency, responsibility, and answerability. Chien (2022), Murshed et al. (2022), and Zhang et al. (2021) explored the determinants and impacts of environmental ac­ counting and management practices, including their relationship with energy efficiency. However, none of these studies delved into the mediation role of energy efficiency on the relationship between EMA and transparency, responsibility, and answerability. Though Rahman and Rahman (2020), Rahman and Islam (2023), Jiao et al. (2023), and Kumalawati et al. (2023) acknowledge the pos­ itive links between EMA and sustainability outcomes, including energy efficiency improvement, limited research has directly examined the mechanism through which energy efficiency mediates the relationship between EMA and specific sustainability dimensions. Jiao et al. (2023), and Kumalawati et al. (2023) EMA’s role in enhancing business sus­ tainability and competitive advantage but did not investigate the mediating effect of energy efficiency. Similarly, Rahman et al. (2021), Ribeiro et al. (2016), and Chien (2022) focused on green intellectual capital, EMA, and energy efficiency but did not specifically address the mediation aspect. While some studies explored the mediating role of energy efficiency in the relationship between sharing economy benefits and sustainable development goals (Chien, 2022), others investigated the moderating and mediating effects of energy efficiency gains on carbon productivity in emerging countries (Murshed et al., 2022) and the road to achieving energy sustainability in Sub-Saharan Africa (Murshed et al., 2022). Additionally, a study examined the mediating role of energy consump­ tion structure in the impact of energy poverty on the energy efficiency of the construction industry (Zhang et al., 2021). Moreover, studies by Rahman et al. (2021), Zhang et al. (2021), and others examined envi­ ronmental accounting practices in developing countries and highlighted the challenges and contextual insights. However, the specific mediating role of energy efficiency in the relationship between EMA and trans­ parency, responsibility, and answerability was not the primary focus of these studies. Thus, the research gap lies in the lack of comprehensive studies that directly investigate how energy efficiency mediates the as­ sociation between EMA practices and accountability dimensions like transparency, responsibility, and answerability. Bridging this gap, the study develops the following hypotheses: responsibility. Compliance with these institutional pressures can be seen as a way for SOEs to gain legitimacy and maintain their reputation as environmentally accountable organizations. Institutional theory pro­ vides a robust framework to understand how external pressures, norms, and values influence organizational behavior and practices (Chaudhry and Amir, 2020). As this study links EMA and energy efficiency on accountability in SOEs in Bangladesh, thus, institutional theory, including the concepts of coercive, mimetic, and normative isomor­ phism, is highly relevant for the study’s context. Coercive isomorphism refers to the adoption of practices or behav­ iors due to external pressures, often in response to regulations, laws, or directives imposed by external authorities (Imtiaz Ferdous et al., 2019). In the context of the study, coercive isomorphism could be observed in how SOEs in Bangladesh respond to environmental regulations and policies set by the government. Bangladesh might have implemented stringent environmental regulations to promote sustainability and accountability in the business sector, including SOEs. Mimetic isomor­ phism involves organizations imitating the practices of successful or reputable organizations in their field, even in the absence of explicit external pressures (Ribeiro and Scapens, 2006). In the study, SOEs in Bangladesh may engage in mimetic behavior by emulating successful private enterprises or multinational companies that have demonstrated environmental responsibility and accountability. Mimetic isomorphism could lead to a spread of sustainable practices across the business landscape, contributing to overall improvements in accountability for environmental impact and performance (Qian and Burritt, 2008). Normative isomorphism refers to the adoption of practices driven by professional norms, values, and beliefs shared within a community or industry (Wang et al., 2019). In the context of the study, normative isomorphism could be observed in how SOEs in Bangladesh, as part of the broader business community, internalize environmental sustain­ ability as a normative value. The broader societal norms and expecta­ tions of environmental responsibility and corporate social responsibility may influence the mindset of SOEs’ managers and stakeholders. Normative isomorphism can contribute to a culture of environmental responsibility within SOEs, enhancing accountability for their environ­ mental impact and performance. Through coercive isomorphism, the study can examine how envi­ ronmental regulations and government policies drive SOEs to adopt EMA and energy efficiency practices, leading to improved environ­ mental accountability. Mimetic isomorphism can help explain the adoption of practices by SOEs based on the imitation of successful pri­ vate enterprises, which could have a positive impact on environmental accountability in the sector. Additionally, normative isomorphism can shed light on how shared societal values and beliefs in environmental responsibility influence SOEs’ decisions to implement sustainable practices and enhance their accountability for environmental perfor­ mance (Imtiaz Ferdous et al., 2019). The hypothesis formation (see Fig. 1) aligns with institutional theory, which emphasizes how external pressures, norms, and beliefs can shape organizational behavior. In this study, EMA and energy efficiency are considered as practices adopted by H8: Energy efficiency mediates the relationship between EMA and transparency. H9: Energy efficiency mediates the relationship between EMA and responsibility. H10: Energy efficiency mediates the relationship between EMA and answerability. 2.5. Theoretical background Institutional theory is a prominent sociological and organizational theory that seeks to understand how organizations and societies func­ tion and evolve based on institutional structures, norms, and rules (Qian and Burritt, 2008). This theory emphasizes the role of institutions in shaping behavior, decision-making, and the overall structure of orga­ nizations. Institutional theory posits that organizations are not isolated entities but are influenced and constrained by the broader social, po­ litical, and cultural contexts in which they operate (Latif et al., 2020; Ribeiro and Scapens, 2006). SOEs in Bangladesh operate within a spe­ cific institutional context characterized by government regulations, so­ cietal expectations, and cultural norms. Institutional pressures, such as governmental policies and environmental regulations, can influence SOEs to adopt EMA practices and enhance their energy efficiency to conform to the prevailing norms and expectations of environmental Fig. 1. Conceptual model. 5 Md.M. Rahman et al. Environmental Challenges 14 (2024) 100832 SOEs in response to external pressures (coercive isomorphism), imita­ tion of successful private enterprises (mimetic isomorphism), and alignment with societal norms (normative isomorphism). By hypothe­ sizing the relationships between EMA, energy efficiency, and account­ ability dimensions (transparency, responsibility, and answerability), the study can examine how these isomorphic mechanisms influence envi­ ronmental performance and accountability in SOEs. associations to improve the sustainability of their sectors or supply chains”. Finally, the study develops an answerability construct using three items: “Engages in stakeholder consultation and feedbacks pro­ cesses to inform its environmental decision-making”, “Provides a clear and accessible channel for stakeholders to report any environmental concerns or incidents”, and “Establishes and communicates clear pro­ cedures for handling and resolving environmental complaints or disputes”. To enhance the instrument’s clarity and comprehensibility, a pre-test was conducted, involving several postgraduate students who provided valuable feedback. Ambiguous items were identified and subsequently revised to refine the instrument (Sarstedt et al., 2022). Following this, a pilot sample comprising 25 undergraduate students was enlisted to assess the reliability, validity, and translational equivalence of the scales. The pilot study allowed us to gage the effectiveness and appro­ priateness of the instrument before proceeding with the full-scale data collection. 3. Methodology 3.1. Research design This study adopts a survey-based research design to collect empirical data from key stakeholders, including finance controllers, internal au­ ditors, accounting professionals, and senior officers of SOEs in Bangladesh. Drawing from established theoretical models, a rigorously designed and validated quantitative questionnaire is utilized. The measurement model of Partial Least Squares Structural Equation Modeling (PLS-SEM) is employed to assess the measurement in­ struments. Additionally, the structural model of PLS-SEM is utilized to test our proposed theoretical framework and hypotheses, offering comprehensive insights into the "net effect" relationships (Kaya et al., 2020). Acknowledging the limitations of conventional symmetric statistical approaches and recognizing the presence of multiple realities in com­ plex causality, the same dataset is subjected to calibration and analysis using fuzzy-set Qualitative Comparative Analysis (fsQCA) (Ragin, 2014). This approach enables us to explore the cause-effect relationships between antecedent conditions and outcomes, providing a holistic perspective on the interdependencies that collectively influence the acceptance of Corporate Accountability and Values (CAVs). By inte­ grating PLS-SEM and fsQCA, we aim to offer a robust and comprehensive analysis of the research questions. Below, we elaborate on the development of instruments, data collection procedures, and rationale for selecting PLS-SEM and fsQCA. 3.3. Data collection The data collection process involved the administration of a selfadministered online survey via Google Forms, a reputable online ques­ tionnaire survey and voting platform, in Bangladesh. The survey was conducted over a period from 15th May to 25th July 2023. The ques­ tionnaire was carefully designed to include concise explanations of the definition and functions of variables, enabling respondents to grasp the concepts effectively (Hair et al., 2017). A total of 200 participants from various SOEs in Bangladesh took part in the survey. After eliminating invalid questionnaires with incomplete data or identical responses, 136 questionnaires were deemed valid and utilized for analysis in this study (see Table 1 for respondents’ profiles). Table 1 presents the detailed demographic profile of the partici­ pating companies and individuals. In terms of gender distribution, the sample exhibited a balanced representation, with 53 % male and 47 % female respondents. Regarding age, the survey attracted a relatively young population, with 20 % of participants aged below 30 years, 40 % between 30 and 40 years, 28 % between 41 and 50 years, and 12 % aged above 50 years. Participants’ years of professional experience were diverse, with 51 % having less than 3 years of experience, 24 % with 3 to 5 years, 18 % with 5 to 10 years, and 8 % with over 10 years of expe­ rience. The respondents also held diverse designations, with 21 % being finance controllers, 14 % internal auditors, 23 % accounting pro­ fessionals, and 43 % senior officers. Common method bias (CMB) is a phenomenon that arises in the context of Partial Least Squares Structural Equation Modeling (PLS- 3.2. Instruments development Ensuring content validity (Sarstedt et al., 2022), the measurement scales utilized in this study were adapted from existing literature and tailored to suit the specific context of EMA. To maintain semantic equivalence (Hair et al., 2019), the translation and back-translation method was employed, thereby ensuring that the essence and meaning of the original language statements were preserved throughout the adaptation process. The constructs under investigation were assessed using a seven-point Likert scale, offering respondents a range of options to express their level of agreement or disagreement (Hair et al., 2017). This study uses four items to reflect EMA adoption from Deb et al. (2022). The energy efficiency construct is comprised of four items taken from Rahman and Islam (2023). This study develops the three constructs (transparency, responsibility, and answerability) for accountability. Transparency construct is developed using four items: “Discloses the environmental performance data on time, such as within three months of the end of the reporting period”, “Reports on the progress towards environmental targets and goals, including any challenges or obstacles encountered”, “Discloses any significant environmental incidents or accidents and provide details on how they were addressed”, and “Pro­ vides detailed information on the supply chain sustainability practices, including the suppliers’ environmental performance”. This study uses four items to reflect the responsibility construct. These are: “Implements a formal environmental management system to manage their environmental risks and opportunities”, “Uses life cycle assessment or other tools to identify the most significant environmental impacts of its operations”, “Regularly reviews and updates its environ­ mental policies and objectives to ensure it remains relevant and effec­ tive”, and “Collaborates with other organizations or industry Table 1 Demographic characteristics (N = 136). Particulars Gender Age Year of Experience Designation Classes Frequencies Percentage Male Female Total Below 30 years 30 - 40 years 41 - 50 years Above 50 years Total Below 3 years 3 - 5 years 5 - 10 years Above 10 years Total Finance controllers Internal Auditors Accounting Professionals Senior Officer Total 72 64 136 27 55 38 16 136 69 32 24 11 136 28 19 31 58 136 53 % 47 % 100 % 20 % 40 % 28 % 12 % 100 % 51 % 24 % 18 % 8% 100 % 21 % 14 % 23 % 43 % 100 % Source: Authors’ input based on primary data collection. 6 Md.M. Rahman et al. Environmental Challenges 14 (2024) 100832 SEM) due to the measurement method employed in a study, rather than being influenced by the underlying causal relationships among variables in the research model. To assess the presence of CMB, a full collinearity assessment approach, as recommended by Kock (2015), is utilized. Ac­ cording to Kock (2015), if all variance inflation factors (VIFs) resulting from the full collinearity test are equal to or lower than 5 (or 3.3 in some cases), it suggests that the model with measurement error can be considered free from CMB. Consequently, the lower the VIF values, the less likely it is that CMB is influencing the study’s outcomes. In the present study, all computed VIFs are found to be below the threshold value of 5, indicating that there is no substantial collinearity issue among the variables due to common method bias. Therefore, based on this assessment, the probability of Common Method Bias can be excluded from our PLS-SEM analysis. By conducting this collinearity assessment and excluding the possibility of CMB, we enhance the robustness and validity of our findings, ensuring that the relationships observed in the model are driven by the genuine interplay of the studied variables, rather than being confounded by methodological factors. and allows for a more nuanced interpretation of the research findings. 4. Results 4.1. Results of PLS-SEM analysis Following the two-step process of PLS-SEM assessment (Kaya et al., 2020), we first evaluated the measurement model and; then, the struc­ tural model. 4.1.1. Measurement model The assessment of the reflective measurement model includes eval­ uating indicator and internal consistency reliability, as well as exam­ ining convergent and discriminant validity (Sarstedt et al., 2022). Indicator reliability, which is determined by squaring the outer loadings of reflective constructs, provides insights into the strength of the rela­ tionship between the latent variable and its observed indicators (Hair et al., 2019). As shown in Table 2, all outer loadings of the reflective constructs surpass the recommended threshold of 0.700 (Hair et al., 2017), indicating satisfactory indicator reliability. The high outer loadings of all indicators demonstrate their strong association with their respective latent constructs, suggesting adequate reliability in measuring the constructs. The internal consistency reliability of the measurement model was meticulously assessed using three different criteria: Cronbach’s alpha (CA), Dijkstra’s PLSc reliability (DPR), and composite reliability (CR) (Hair et al., 2017; Kaya et al., 2020). The results, as presented in Table 3, demonstrate that all three measures exceed the recommended threshold of 0.7, indicating excellent measurement reliability (Hair et al., 2019; Md M. Rahman, 2023). The impressive values of the composite reli­ ability (CR), Cronbach’s alpha (CA), and Dijkstra’s PLSc reliability (DPR) reaffirm the consistency and dependability of the measurement model in capturing the latent constructs accurately. Furthermore, convergent validity, a crucial aspect of measurement validity, was evaluated based on the average variance extracted (AVE) (Kaya et al., 2020). The values in Table 3 reveal that the AVE exceeds the desired threshold of 0.5, underscoring the model’s good convergent validity (Hair et al., 2019). Discriminant validity, a critical aspect of construct validity, was rigorously assessed using multiple criteria, including the Fornell-Larcker criterion (Fornell and Larcker, 1981), heterotrait-monotrait (HTMT) ratio of the correlations, and cross-loadings criterion. These stringent evaluations ascertain the extent to which each construct is distinct from others empirically. The Fornell-Larcker criterion necessitates that the square root of the average variance extracted (AVE) for each construct 3.4. Data analysis approach The data analysis in this study involved the use of two distinct methodologies: Partial Least Squares Structural Equation Modeling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). 3.4.1. PLS-SEM approach For estimating the measurement and structural model, PLS-SEM was employed (Hair et al., 2017). PLS-SEM is known for its exceptional flexibility in handling various modeling complexities, such as formative constructs and intricate models. Moreover, it is well-suited for datasets with small sample sizes and non-normally distributed data (Hair et al., 2017). Due to these advantageous features, PLS-SEM has gained wide popularity and has been extensively applied in diverse research do­ mains, including organization management, information management (Sarstedt et al., 2022), and environmental management (Deb et al., 2022). Given our research objective to identify key "driver" constructs and considering the complexity of our proposed structural model, we found PLS-SEM to be the most appropriate approach. Specifically, we utilized the software Warp PLS 8, adhering to recommended guidelines (Hair et al., 2017). 3.4.2. QCA approach The Qualitative Comparative Analysis (QCA), originally developed by Ragin (2014), is a robust methodology for conducting in-depth an­ alyses of causal contributions from different conditions to a specific outcome of interest, based on set theory principles (Wang et al., 2021). QCA is particularly adept at handling various forms of complex causa­ tion, including configurations of causal conditions, equi-finality (where multiple causal pathways lead to the same outcome), multi-finality (where identical conditions result in different outcomes), and causal asymmetry (where the causes of failure may not simply be the absence of the causes of success) (Kaya et al., 2020; Ragin, 2014). PLS-SEM and fsQCA operate on distinct principles. PLS-SEM follows a variable-oriented approach, using regression analyses to verify the net effect and significance of each independent variable on the dependent variable (Wang et al., 2021). However, it does not determine which variables are sufficient or necessary for a particular outcome. On the other hand, fsQCA adopts a case-oriented approach, analyzing the causal contributions of different conditions (Pappas and Woodside, 2021). As a complementary analysis to PLS-SEM, fsQCA is particularly suited for situations where unobserved heterogeneity effects are detec­ ted, as it elucidates how various factors work in conjunction to produce a specific outcome (Fiss, 2007). Therefore, we employ both symmetrical approaches with PLS-SEM and asymmetrical approaches with fsQCA to empirically test proposed models (Wang et al., 2021). This combined analytical approach enhances the rigor and depth of our investigation Table 2 Outer loadings (Bolded-Italic value) and cross-loadings. EMA1 EMA2 EMA3 EMA4 ENE1 ENE2 ENE3 ENE4 TRC1 TRC2 TRC3 TRC4 RES1 RES2 RES3 RES4 ANS1 ANS2 ANS3 7 EMA ENE TRC RES ANS 0.840 0.834 0.773 0.846 0.564 0.455 0.339 0.407 0.446 0.529 0.422 0.566 0.409 0.541 0.534 0.598 0.591 0.339 0.41 0.401 0.523 0.389 0.561 0.781 0.826 0.780 0.703 0.512 0.573 0.443 0.597 0.601 0.583 0.594 0.671 0.619 0.596 0.655 0.527 0.47 0.454 0.535 0.623 0.457 0.405 0.551 0.847 0.859 0.823 0.773 0.539 0.618 0.629 0.652 0.658 0.411 0.54 0.535 0.529 0.359 0.614 0.678 0.508 0.575 0.507 0.613 0.599 0.515 0.633 0.849 0.794 0.863 0.835 0.745 0.547 0.636 0.456 0.467 0.316 0.449 0.564 0.614 0.605 0.453 0.535 0.554 0.398 0.519 0.683 0.503 0.583 0.715 0.803 0.861 0.909 Md.M. Rahman et al. Environmental Challenges 14 (2024) 100832 Table 3 Internal consistency, convergent validity, and full collinearity. Composite reliability (CR) Cronbach’s alpha (CA) Dijkstra’s PLSc reliability (DPR) Average variances extracted (AVE) Full collinearity VIFs EMA ENE TRC RES ANS 0.894 0.842 0.855 0.679 1.813 0.856 0.775 0.784 0.599 2.738 0.879 0.815 0.819 0.647 2.435 0.902 0.856 0.86 0.698 2.449 0.894 0.821 0.831 0.738 2.678 Note: EMA=Environmental management accounting, ENE=Energy efficiency, TRC=Transparency, RES=Responsibility, ANS=Answerability, VIFs=Variance inflation factors. should exceed the correlations between that construct and other con­ structs (Hair et al., 2019). Additionally, the cross-loadings criterion demands that the factor loading for each indicator within a construct should surpass all cross-loadings with other constructs. Lastly, the HTMT criterion establishes that the HTMT ratio should be significantly lower than the threshold values of 0.90 or 0.85 (Hair et al., 2019). As high­ lighted in Tables 2 and 4, all of these discriminant validity criteria have been satisfied, affirming the distinctiveness and independence of each construct from others. This robust validation of discriminant validity bolsters the credibility of our measurement model and provides strong evidence that the constructs are effectively capturing unique and distinct dimensions of the underlying theoretical constructs. 4.1.2. Structural model The assessment of the structural model incorporates essential criteria, including the coefficient of determination (R2) and the signif­ icance and relevance of the path coefficients, as recommended by Hair et al. (2019) and Sarstedt et al. (2022). Before conducting the assess­ ment, multicollinearity is thoroughly examined through the variance inflation factor (VIF), as suggested by Hair et al. (2019). In this regard, Table 3 demonstrates that all VIF values remain between 1.813 and 2.738, which are significantly below the critical value of 3. This obser­ vation confirms the absence of multicollinearity issues, further enhancing the robustness of our analysis. To ensure the stability and reliability of the study results, the statistical significance of various PLS-SEM outcomes was rigorously tested using the Warp PLS 8 software. The final results of the structural model assessment are presented in Fig. 2, providing valuable insights into the explained variance of the endogenous variables (R2) and the standardized path coefficients (β). In PLS-SEM research, R-squared is a crucial metric used to gage the explanatory power of the model, representing the variance explained in each endogenous construct Hair et al. (2019). While R2 is convention­ ally employed for assessing the goodness-of-fit in regression analysis (Sarstedt et al., 2022), in our study, it serves as a measure of how well our proposed model accounts for the variability in the key constructs. Table 5 vividly portrays the outcomes of our analysis, showcasing that our proposed model successfully explains a substantial amount of vari­ ance (R-squared) in various constructs. Specifically, the model accounts for 34 % of energy efficiency, 53 % of transparency, 54 % of re­ sponsibility, and an impressive 60 % of answerability. Moreover, the average R-square value across all constructs is 50.10 %, indicating a moderate yet noteworthy explanatory power (Hair et al., 2019). These Fig. 2. Structural model analysis. Table 5 Model evaluation through R-squared, Q-squared, and F-squared. ENE TRC RES ANS EMA ENE TRC RES ANS 0.824 0.571 0.603 0.622 0.515 0.705 0.774 0.654 0.733 0.726 0.739 0.839 0.804 0.729 0.621 0.731 0.802 0.883 0.836 0.744 0.624 0.808 0.771 0.892 0.859 Adjusted R-squared Q-squared F-squared 0.341 0.525 0.596 0.59 0.336 0.518 0.542 0.535 0.344 0.527 0.6 0.543 0.341 (0.219–0.306) (0.187–0.409) (0.076–0.466) R-squared values provide compelling evidence of the model’s effec­ tiveness in capturing the underlying relationships between EMA, energy efficiency, transparency, responsibility, and answerability in SOEs. The substantial explanatory power of the model emphasizes its ability to elucidate and comprehend the complexities within the investigated phenomenon. Q-squared is a critical metric used to assess the model’s predictive validity and generalizability (Hair et al., 2019). It quantifies the extent to which the model’s predictions align with the observed values of the dependent variable (endogenous construct) based on the independent variables. Higher Q-squared values indicate a stronger ability of the model to make accurate predictions and validate its performance beyond the sample used for model estimation (Kaya et al., 2020). In Table 5, the Q-squared values for energy efficiency, transparency (TRC), responsibility (RES), and answerability (ANS) are 0.344, 0.527, 0.600, and 0.543, respectively. These values signify that the model’s pre­ dictions are highly reliable and possess robust predictive validity, enhancing our confidence in its effectiveness in real-world scenarios. F-squared is a valuable metric used to assess the unique contribution of each exogenous construct (independent variable) to explaining the variance in the dependent variable (endogenous construct) (Hair et al., 2017). It measures the proportion of variance in the endogenous construct that is exclusively attributed to each specific predictor. The F-squared values are provided as ranges, indicating the possible varia­ tion in the contributions of individual constructs. For instance, in Table 5, the F-squared values for transparency (TRC), responsibility (RES), and answerability (ANS) are indicated within ranges Table 4 Discriminant validity through the Fornelle–Larcker criterion and HTMT ratio. EMA ENE TRC RES ANS R-squared Note: The bolded-Italic diagonal is AVE’s square root and above the diagonal is the HTMT ratio. 8 Md.M. Rahman et al. Environmental Challenges 14 (2024) 100832 (0.219–0.306) and (0.187–0.409), and (0.076–0.466) respectively. These ranges suggest that different exogenous constructs have varying degrees of impact on explaining the variance in the respective endoge­ nous constructs. Such insights allow us to discern the unique signifi­ cance of each predictor in influencing the studied outcomes. According to Table 6, the PLS analysis shows that EMA has a sta­ tistically significant positive effect on transparency (TRC) (β = 0.355, p < 0.001). This result supports the hypothesis (H1) that EMA positively influences the level of transparency in SOEs. Similarly, EMA has a sta­ tistically significant positive effect on responsibility (RES) (β = 0.300, p < 0.001). The result supports the hypothesis (H2) that EMA has a positive impact on promoting responsibility in SOEs. Finally, EMA has a statistically significant positive effect on answerability (ANS) (β = 0.146, p < 0.05). The result supports the hypothesis (H3) that EMA contributes to increasing the level of answerability in SOEs. Energy efficiency has a statistically significant positive effect on transparency (TRC) (β = 0.462, p < 0.001). The result confirms the hypothesis (H4) that energy efficiency positively impacts transparency in SOEs. Energy efficiency has a statistically significant positive effect on responsibility (RES) (β = 0.559, p < 0.001). The result supports the hypothesis (H5) that energy efficiency promotes responsibility in SOEs. Energy efficiency has a statistically significant positive effect on answerability (ANS) (β = 0.641, p < 0.001). The result confirms the hypothesis (H6) that energy efficiency positively influences the level of answerability in SOEs. EMA has a statistically significant positive effect on energy efficiency (β = 0.584, p < 0.001). The result supports the hypothesis (H7) that EMA positively affects energy efficiency in SOEs. EMA positively influences transparency (TRC) through the medi­ ating effect of energy efficiency (β = 0.270, p < 0.001). This result supports the hypothesis (H8) that EMA indirectly promotes trans­ parency by enhancing energy efficiency. EMA positively influences re­ sponsibility (RES) through the mediating effect of energy efficiency (β = 0.326, p < 0.001). The result confirms the hypothesis (H9) that EMA indirectly promotes responsibility through improved energy effi­ ciency. EMA positively influences answerability (ANS) through the mediating effect of energy efficiency (β = 0.375, p < 0.001). The result supports the hypothesis (H10) that EMA indirectly enhances answer­ ability by fostering energy efficiency. Table 6 summarizes the results for the 10 hypotheses. 4.2.1. Calibration The calibration process in fsQCA involves transforming raw data into fuzzy sets, which represent the degree of membership or nonmembership of cases in a set. In this study, the raw data is converted into fuzzy sets that range from zero (representing full exclusion from a set) to one (representing full inclusion) (Kaya et al., 2020). To achieve this, an index is calculated for each construct by averaging the corre­ sponding indicators. The calibration of the fuzzy sets requires the specification of three anchors: full membership, full non-membership, and a crossover point. In this study, the direct method is used for calibrating all constructs (conditions and outcome) based on theoretical anchors, such as those used in previous research (Kaya et al., 2020). Specifically, a rating of seven is considered as full membership, a rating of one as full non-membership, and a rating of four as the crossover point. To ensure accuracy and avoid any potential issues with scores exactly equal to 0.50, this study follows the approach proposed by Fiss (2007) by adding a small value of 0.001 to such scores. This ensures that no cases are dropped from the analysis due to their proximity to the crossover point. The calibration process is automated in fsQCA 3.0, and the results are presented in Table 7, providing the necessary fuzzy sets for further analysis of causal conditions and outcomes. 4.2.2. Analysis of necessary conditions The analysis of sufficient conditions is a fundamental aspect of fsQCA, but it is essential to begin by identifying necessary conditions before delving into sufficient conditions (Ragin, 2009). In this study, the focus is on three endogenous variables, namely transparency (TRC), responsibility (RES), and answerability (ANS), which are considered outcome conditions in the fsQCA analysis. Similarly, the two antecedent conditions in the SEM model, EMA, and energy efficiency, are also considered in the fsQCA analysis. To determine whether any of the two antecedent conditions, EMA and ENE, are necessary for the occurrence of TRC, RES, or ANS, the study examines whether these conditions are always present (or always absent) in all cases where the respective outcome is present (or absent) (Ragin, 2014). In other words, the achievement of TRC, RES, or ANS is contingent on the occurrence of the specific antecedent condition. The degree of conformity to this rule is reflected in the concept of "consistency." For a condition to be classified as "necessary" or "almost always necessary," its corresponding consistency score must surpass the threshold values of 0.9 or 0.8, respectively (Ragin, 2006). By analyzing the results presented in Table 8, it becomes evident that both EMA and ENE are necessary conditions for the outcomes of TRC, RES, and ANS. This underscores the significance of these antecedent conditions in influencing the occurrence of transparency, responsibility, and answerability in the context of SOEs. The identification of necessary conditions in fsQCA provides valuable insights into the underlying causal mechanisms, and it paves the way for further analysis of sufficient conditions to understand the complex interplay of factors that lead to the acceptance and adoption of EMA and energy efficiency in SOEs. 4.2. Results for qualitative comparative analysis The same constructs and datasets used in the PLS-SEM analysis were subjected to fsQCA, providing a comprehensive comparison with the earlier presented PLS-SEM results. The fsQCA analysis followed key procedures, emphasizing model development, sampling, data calibra­ tion, analysis of necessary conditions, analysis of sufficient conditions, and the interpretation of the findings (Pappas and Woodside, 2021). Table 6 Hypothesis test summary. Hypothesis H1 H2 H3 H4 H5 H6 H7 H8 H9 H10 Structural path Direct effects EMA→TRC EMA→RES EMA→ANS ENE→TRC ENE→RES ENE→ANS EMA→ENE Mediating effects EMA→ENE→TRC EMA→ENE→RES EMA→ENE→ANS β SE p-value Supported 0.355 0.300 0.146 0.462 0.559 0.641 0.584 0.079 0.080 0.083 0.077 0.075 0.074 0.075 0.001*** 0.001*** 0.040** 0.001*** 0.001*** 0.001*** 0.001*** Yes Yes Yes Yes Yes Yes Yes 0.270 0.326 0.375 0.057 0.056 0.056 0.001*** 0.001*** 0.001*** Yes Yes Yes 4.2.3. Analysis of sufficient conditions The analysis of sufficient conditions commences by constructing a truth table (Ragin, 2014). This truth table contains 2k rows, where k represents the number of conditions, and each row corresponds to a Table 7 Data calibration. EMA ENE TRC RES ANS Note: β=Coefficient value, SE=Standard Error, ***=p<0.001, and **=p<0.05. EMA=Environmental management accounting, ENE=Energy efficiency, TRC=Transparency, RES=Responsibility, ANS=Answerability,. 9 Full nonmembership Crossover point Full membership 1 1 1 1 1 4 4 4 4 4 7 7 7 7 7 Md.M. Rahman et al. Environmental Challenges 14 (2024) 100832 Table 8 Necessary conditions for transparency, responsibility, and answerability. Outcome Transparency (TRC) Causal configuration EMA ENE Solution coverage Solution consistency Consistency cutoff Frequency cutoff RC 0.809 0.858 Responsibility (RES) UC 0.061 0.110 0.919 0.801 0.857 16 Con 0.849 0.843 RC 0.800 0.855 UC 0.057 0.116 0.912 0.837 0.875 16 Answerability (ANS) Con 0.880 0.884 RC 0.801 0.853 UC 0.495 0.132 0.902 0.825 0.847 16 Con 0.848 0.879 Note: ‘*’ indicates the logical operator AND. RC=Row Coverage, UC=Unique Coverage, and Con=Consistency. unique configuration of conditions (Kaya et al., 2020). For each obser­ vation in the dataset, based on the set membership scores, it is assigned to a specific row in the truth table. In this study, the fsQCA algorithm is utilized to generate truth tables for each of the three outcomes, namely transparency (TRC), responsibility (RES), and answerability (ANS) (refer to Tables 9–11). To distill meaningful configurations from the truth tables, the study employs a frequency threshold of 16 observations to exclude configurations with limited relevance (Wang et al., 2021). It is crucial to ensure that at least 80 % of the cases in the sample remain after applying the frequency restriction, as recommended in the QCA literature (Ragin, 2014). Consequently, the frequency threshold ensures that 85.7 %, 87.5 %, and 84.7 % of the cases in the sample are included in the analyses for TRC, RES, and ANS, respectively. The subsequent step involves identifying which configurations are sufficient for achieving the desired outcomes. To accomplish this, the study applies a consistency threshold of greater than or equal to 0.80 along with a PRI (Parsimonious Solution) score threshold of greater than or equal to 0.80 (Ragin, 2014). These thresholds prevent the occurrence of simultaneous subset relations between attribute combinations in both the outcomes and their negations, ensuring robust and unbiased results (Kaya et al., 2020). Furthermore, the fsQCA software provides three solution types: an intermediate solution, a parsimonious solution, and a complex solution. In this study, the intermediate solutions (Table 9) are analyzed for the three outcomes, as these solutions avoid making simplifying assumptions and provide a comprehensive analysis (Ragin, 2009). The intermediate solutions demonstrate that both the consis­ tency and coverage values for each configuration surpass the minimum acceptable threshold (Ragin, 2009), thereby strengthening the validity and reliability of the findings. Table 10 Sufficient conditions for responsibility. Causal condition EMA ENE TRC ANS Raw consist. PRI consist. SYM consist. EMA ENE TRC RES Raw consist. PRI consist. SYM consist. 2 3 4 ⬤ 〇 〇 ⬤ 〇 〇 0.909 0.809 0.853 0.877 0.552 0.565 0.857 0.530 0.548 0.658 0.213 0.219 4 〇 ⬤ 〇 〇 0.918 0.835 0.871 0.878 0.622 0.632 0.847 0.482 0.484 0.683 0.250 0.268 Configurations for ANS 1 2 3 4 ⬤ ⬤ ⬤ 〇 〇 ⬤ 〇 〇 0.918 0.835 0.871 0.878 0.622 0.632 0.847 0.482 0.484 0.683 0.250 0.268 Note. Black (“⬤”) and hollow circles (“〇”) show the presence and absence of a condition, respectively. Blank cells show a “do not care” situation. The analysis reveals a positive and statistically significant relation­ ship between EMA and transparency. This finding suggests that orga­ nizations that adopt EMA practices tend to exhibit higher levels of transparency in their operations. This has significant implications for stakeholders as it indicates that companies that prioritize environmental accounting are likely to be more open and accountable in disclosing their environmental impact, performance, and initiatives (Bebbington et al., 2014). Increased transparency can enhance trust and credibility among stakeholders and foster better decision-making, which may lead to improved environmental performance and responsible business practices (Deb et al., 2023; Islam et al., 2023). The study also finds a positive and statistically significant association between EMA and Re­ sponsibility. This implies that organizations that integrate EMA into their practices are more likely to demonstrate a strong commitment to environmental responsibility (Chien, 2022). Emphasizing environ­ mental responsibility can lead to better resource management, waste reduction, and compliance with environmental regulations. The findings suggest that companies adopting EMA are more inclined to adopt environmentally responsible practices, which can enhance their repu­ tation, attract environmentally-conscious customers, and contribute positively to sustainability objectives. Further, the analysis indicates a positive and statistically significant link between EMA and Answer­ ability. This suggests that organizations incorporating EMA practices are Configurations for TRC ⬤ ⬤ 3 ⬤ 〇 Causal condition Table 9 Sufficient conditions for transparency. EMA ENE RES ANS Raw consist. PRI consist. SYM consist. 2 ⬤ ⬤ Table 11 Sufficient conditions for answerability. The PLS-SEM analysis provides valuable insights into the relation­ ships among EMA, energy efficiency, transparency, responsibility, and answerability. The findings suggest that organizations incorporating environmental accounting practices and prioritizing energy efficiency are likely to exhibit greater transparency, responsibility, and answerability. 1 1 Note. Black (“⬤”) and hollow circles (“〇”) show the presence and absence of a condition, respectively. Blank cells show a “do not care” situation. 5. Discussion Causal condition Configurations for RES Note. Black (“⬤”) and hollow circles (“〇”) show the presence and absence of a condition, respectively. Blank cells show a “do not care” situation. 10 Md.M. Rahman et al. Environmental Challenges 14 (2024) 100832 consistently contribute to improved environmental outcomes. This highlights the need for a holistic approach to environmental manage­ ment, where organizations integrate various practices to address mul­ tiple environmental dimensions effectively. more likely to exhibit higher levels of answerability. This has important implications as it indicates that companies embracing EMA are likely to be more accountable and responsive to the environmental concerns of their stakeholders. This increased answerability can foster a positive relationship with stakeholders and lead to greater support and trust from customers, investors, and communities. The results show a positive and statistically significant relationship between Energy Efficiency and Transparency. This suggests that orga­ nizations prioritizing energy efficiency are more likely to demonstrate higher levels of transparency in their operations. Increased transparency about energy-efficient practices can highlight the organization’s commitment to sustainability and responsible energy consumption. Enhanced transparency regarding energy efficiency initiatives can improve the company’s reputation, attract environmentally-conscious consumers, and promote a competitive advantage in the market (Deb et al., 2022). The analysis also reveals a positive and statistically sig­ nificant association between Energy Efficiency and Responsibility. This implies that organizations emphasizing energy efficiency are more likely to demonstrate a strong commitment to environmental responsibility. Emphasizing energy efficiency can result in reduced carbon emissions, resource conservation, and cost savings. Companies that prioritize en­ ergy efficiency are likely to be perceived as environmentally respon­ sible, which can enhance their brand image and attract environmentally-conscious consumers and investors. Further, the study finds a positive and statistically significant link between Energy Efficiency and Answerability. This suggests that organizations priori­ tizing energy efficiency are more likely to exhibit higher levels of answerability to their stakeholders. Being more accountable regarding energy efficiency practices can create a positive image of the company and foster trust among customers, investors, and communities. Increased answerability can also lead to better collaboration with stakeholders and greater support for sustainability initiatives (Hawrysz and Foltys, 2015). The analysis indicates a positive and statistically significant rela­ tionship between EMA and Energy Efficiency. This implies that organi­ zations that adopt EMA practices are more likely to prioritize energy efficiency in their operations. Integrating EMA and energy efficiency can lead to better resource utilization, waste reduction, and overall envi­ ronmental performance. This finding suggests that environmental ac­ counting practices play a role in fostering energy-conscious behavior within organizations (Kaur and Lodhia, 2019). The results demonstrate the mediating effects of Energy Efficiency on the relationship between EMA and the outcome variables of Transparency, Responsibility, and Answerability. This implies that part of the effects of EMA on these outcomes is channeled through its impact on energy efficiency practices. These mediating effects suggest that promoting energy efficiency can be an effective strategy to enhance transparency, responsibility, and answerability in organizations that adopt EMA practices. The fsQCA analysis provides valuable insights into the complex re­ lationships among EMA, Energy efficiency, Transparency (TRC), Re­ sponsibility (RES), and Answerability (ANS). Overall, the findings suggest that both EMA and ENE are necessary conditions for achieving higher levels of Transparency, Responsibility, and Answerability in or­ ganizations. This indicates that organizations cannot solely rely on one of these conditions to enhance their environmental performance and accountability. Instead, a comprehensive approach that integrates both EMA and ENE practices is essential for fostering transparency, demon­ strating responsibility, and promoting answerability towards environ­ mental matters. The fsQCA analysis also identifies specific configurations of EMA and ENE that lead to positive environmental outcomes. By recognizing the sufficient conditions for achieving Transparency, Responsibility, and Answerability, organizations can tailor their strategies and actions to optimize their environmental performance. Furthermore, the fsQCA analysis underscores the importance of considering the joint effects of EMA and ENE practices, as certain combinations of these conditions 6. Conclusions, implications, and future study direction 6.1. Conclusions This study investigated the relationship between EMA, Energy effi­ ciency, transparency, responsibility, and answerability in organizations, utilizing both Partial Least Squares Structural Equation Modeling (PLSSEM) and Fuzzy Set Qualitative Comparative Analysis (fsQCA). The findings shed light on the complex interplay between these variables and provide valuable insights into enhancing environmental performance and accountability. The PLS-SEM analysis revealed significant positive relationships between EMA and ENE with transparency, responsibility, and answerability. These results indicate that organizations adopting EMA and ENE practices are more likely to exhibit higher levels of transparency, demonstrate greater responsibility towards environ­ mental matters, and be more answerable to stakeholders for their accountability. Furthermore, the study identified mediating effects of ENE on the relationships between EMA and the outcomes, highlighting the importance of energy efficiency as a pathway through which EMA practices influence environmental performance. The fsQCA analysis further supported the importance of both EMA and ENE as necessary conditions for achieving positive environmental outcomes. Organizations need to integrate both EMA and ENE practices to foster transparency, responsibility, and answerability effectively. The fsQCA findings also identified specific configurations of EMA and ENE that lead to desirable environmental outcomes, emphasizing the need for a comprehensive approach to environmental management. The combined findings from PLS-SEM and fsQCA provide a nuanced un­ derstanding of the complex interactions between EMA, ENE, and envi­ ronmental performance dimensions. Organizations can use this knowledge to develop tailored sustainability strategies that optimize environmental performance and accountability. By embracing both EMA and ENE practices, organizations can not only reduce environ­ mental impacts but also strengthen their reputation and stakeholder relationships. 6.2. Implications The findings of this study have several important managerial impli­ cations for organizations, particularly SOEs operating in contexts like Bangladesh. Firstly, managers should recognize the significance of EMA and Energy efficiency practices in promoting accountability within their organizations. By implementing EMA systems and focusing on energyefficient operations, organizations can enhance transparency, re­ sponsibility, and answerability to stakeholders, fostering a positive image and reputation. Secondly, the study highlights the interplay be­ tween EMA and ENE as mediating factors for achieving positive envi­ ronmental outcomes. Managers should consider integrating these practices into their overall sustainability strategies to maximize their impact on accountability and environmental performance. Thirdly, the study underscores the necessity of both EMA and ENE in achieving accountability. Managers should avoid viewing these prac­ tices in isolation and instead adopt a holistic approach to sustainable management. Integrating EMA and ENE efforts can lead to more comprehensive and effective environmental stewardship, satisfying stakeholders’ expectations and regulatory requirements. Lastly, the study’s focus on SOEs is significant. Managers in such organizations should be aware of their unique position in terms of accountability to the public and government authorities. By embracing EMA and ENE prac­ tices, SOEs can demonstrate their commitment to social and environ­ mental responsibility, further solidifying their role as responsible and 11 Environmental Challenges 14 (2024) 100832 Md.M. Rahman et al. sustainable entities. environmental performance for mining companies listed in China. Environ. Dev. Sustain. 23, 12192–12216. files/598/s10668-020-01164-4.html. Ahern, E., Desai, A., & Jimenez-Bescos, C. (2018). Enhancing building energy efficiency with accountable system of building regulations compliance. Ahmed, Z., Adebayo, T.S., Udemba, E.N., Murshed, M., Kirikkaleli, D., 2022. Effects of economic complexity, economic growth, and renewable energy technology budgets on ecological footprint: the role of democratic accountability. Environ. Sci. Pollut. 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Secondly, the study’s reliance on a small sample size may limit the statistical power and generalizability of the results. Future research with larger sample sizes could provide more robust and comprehensive insights into the relationships under investigation. Thirdly, the study adopted a crosssectional design, which limits the establishment of long-run relation­ ships between the variables. Conducting longitudinal studies or exper­ imental research would enable the exploration of the dynamic and onrun nature of the relationships. Furthermore, investigating the role of organizational culture, leadership, and corporate governance in facili­ tating the adoption and effectiveness of EMA and ENE practices would provide a more comprehensive understanding of the drivers of accountability in organizations. For future study scope, researchers could explore the moderating factors that influence the relationships between EMA, ENE, and accountability. Additionally, comparative studies across different industries or sectors could shed light on sectorspecific implications and challenges in promoting sustainability and accountability. Ethical approval Not applicable. Consent to participate Not applicable. Consent to publish Not applicable. Funding This research receives no external funding. CRediT authorship contribution statement Md. Mominur Rahman: Writing – review & editing, Writing – original draft, Visualization, Validation, Resources, Project administra­ tion, Methodology, Investigation, Formal analysis, Conceptualization. Shuvabrata Saha: Visualization, Data curation. Mahfuzul Hoque: Supervision. Declaration of competing interest The author declares that there is no competing interest. Data availability Data and materials are available upon reasonable request through the corresponding author. References Agyemang, A.O., Yusheng, K., Twum, A.K., Ayamba, E.C., Kongkuah, M., Musah, M., 2021. 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