Barriers to digital transformation for circular transition in the cement industry: An emerging economy perspective

Abstract

Despite the critical role of cement manufacturing industries in infrastructure development, its contribution to a significant share of global carbon emissions underscores the urgency of integrating sustainable practices. Digital transformation offers potential to enhance transparency, resource efficiency, and circular economy transitions, yet its implementation faces significant challenges. This study examines the barriers impeding the adoption of digital transformation in the cement manufacturing industry of emerging economies, with particular attention to Bangladesh. Through a systematic literature review and expert validation, seventeen key barriers were identified and assessed using the Interval-Valued Pythagorean Fuzzy DEMATEL (IVPF-DEMATEL) method. The analysis highlights “limited flexibility in reverse logistics” and “lack of environmental commitment among top management” as the most prominent barriers, while “reluctance to invest in recycling” and “inefficient management practice” emerge as critical causal factors. The findings provide a structured understanding of the interdependencies among these barriers, enabling policymakers, practitioners, and industry leaders to prioritize root causes over symptomatic effects. This research contributes to the limited body of knowledge on digital transformation in the cement sector of emerging economies and offers practical pathways for advancing sustainability through the adoption of digital transformation.

Keywords

digital transformation circular economy cement industry emerging economies IVPF-DEMATEL

1. Introduction

The cement industry is an essential part of the economic growth and infrastructure development of emerging economies. It plays a key role in supporting industrialization, urbanization, and construction. However, cement production also brings serious environmental challenges. The process of manufacturing cement releases a large amount of carbon dioxide. It is responsible for almost 10 percent of global carbon emissions, which is a major cause of global warming.¹ These emissions create serious threats to the environment and contradict the goals of the Paris Agreement that aims to limit the global temperature increase to below 1.5 degrees Celsius.² Bangladesh, being a signatory to the Paris 2015 Agreement, must take effective steps to reduce these emissions and focus on climate mitigation strategies. In this context, digital transformation has become an important approach for improving sustainability in the cement sector. Digital transformation refers to the systematic integration of digital technologies such as data analytics, Internet of Things (IoT), digital traceability systems, and supply chain information platforms into core operational and managerial processes. It helps connect and integrate the different stakeholders involved in cement production. Through digital technologies, transparency and reliability can be improved across every part of the supply chain. This allows better monitoring of operations and supports the implementation of environmentally responsible practices. Despite these advantages, many challenges still prevent the cement industry from adopting digital systems. The main difficulties include cultural resistance, lack of infrastructure, and limited awareness among industry leaders.³

To address environmental concerns, many organizations have started applying the concept of the Circular Economy (CE) in the cement industry. The circular economy focuses on ensuring that environmental benefits go together with business growth and profitability.⁴ It helps reduce greenhouse gas emissions by about 63 percent and may contribute up to 25 trillion dollars to the global economy by 2050.⁴ With the rise of global population, the consumption pattern of construction commodities has been experiencing proportionate upward momentum, with the need to develop the civil infrastructure to accommodate the needs of people. The circular economy approach to building materials entails a seamless and uninterrupted movement of materials throughout the whole lifecycle, including purchase, utilization, deconstruction or dismantling, reuse, recycling, and recovery.⁵

While servitization literature emphasizes a shift from product-centric to service-centric business models, this study focuses on the broader digital transformation required to enable circular transition within the cement industry. In emerging economies such as Bangladesh, firms are still at an early stage of digital maturity, where foundational digital integration across supply chains and management systems precedes advanced servitized business models.⁶

Digitalization of the supply chain can play a vital role in achieving this transformation. It connects different functions and professionals in the manufacturing process and allows them to share data more effectively.³ With digital systems, both the information and the status of a product are available in real time.⁷ Studies such as Anshassi and Townsend⁸ have examined how digital tools can improve waste estimation, while Seyyedi et al.⁹ have proposed digital methods for waste reuse in organizations. Unlike the traditional linear model of production that leads to high waste generation, a circular approach encourages recycling and better resource utilization. As environmental awareness increases, cement industries are under pressure to innovate. Digital transformation can therefore become a powerful driver that supports the shift toward circular and sustainable practices.

Researchers have recently shown greater interest in sustainability within the cement sector. However, most studies have concentrated on the Triple Bottom Line (TBL) framework, focusing mainly on environmental, social, and economic aspects. For example, Ighalo and Adeniyi¹⁰ and Karttunen et al.¹¹ studied environmental innovation and sustainability practices. Similarly, Ada et al.⁴ and AlJaber et al.⁵ examined the barriers and enablers for adopting a circular economy in the cement industry.

Although prior studies have examined circular economy barriers and sustainability practices in the cement industry, they do not investigate the interrelated barriers to digital transformation that enable circular transition, particularly in emerging economies. Research in developed countries has already explored digital integration to some extent, but there is still a lack of research on how emerging economies can adopt digital transformation and what barriers they face in doing so. Existing literature largely treats digitalization and sustainability challenges independently, without analyzing their causal interdependencies using structured decision-making methods. This study aims to fill this research gap by identifying and ranking the barriers that limit the adoption of digital transformation in the cement industry from the perspective of an emerging economy. It also seeks to provide a structured understanding of how digital innovation can be used to reduce greenhouse gas emissions and promote sustainability in cement production. To achieve these objectives, the study answers the following research questions:

RQ1. What are the barriers to adoption of digital transformation in the cement sector to address climate mitigation needs?

RQ2. What is the relative importance of the identified barriers to digitization in the cement industry to address sustainability concerns?

RQ3. What steps must be taken to effectively reduce or eliminate these barriers?

To answer these questions, the study identifies potential barriers through a detailed review of existing literature. These barriers are then verified through expert interviews and analyzed using the Interval Valued Pythagorean Fuzzy DEMATEL (IVPF-DEMATEL) method. This analytical method helps to explore the relationships among the barriers and determine which ones have the most significant influence. It also allows the prioritization of barriers so that decision makers can focus on the most critical factors. Through this approach, the study aims to provide meaningful guidance for policymakers and practitioners in optimizing the use of resources, energy, and time within the cement industry.

2. Literature review

A comprehensive review of existing literature is essential to establish the theoretical foundation of this study and to identify the key research gaps. This section synthesizes prior academic contributions related to the integration of digital technologies and sustainability in the cement industry. The review focuses on three major themes that are directly relevant to the objectives of this research. The first theme explores the role of supply chain digitization and its potential to enhance operational efficiency, transparency, and sustainability performance. The second theme examines the existing sustainability practices within the cement industry, highlighting efforts toward achieving circular economy objectives. The third theme investigates the barriers that hinder the adoption of digital transformation, particularly in the context of emerging economies. Together, these areas provide a coherent understanding of how digital transformation and sustainability principles intersect within the cement sector and reveal the existing gaps that this study aims to address.

2.1. Digitization in supply chain

Digitization has become essential for business survival and competitiveness in the modern world.¹² The process of digitalization provides several advantages across the supply chain. It improves access to information, supports better optimization of logistics, enables real time data collection, and enhances inventory management and transparency.¹³ The implementation of robotic process automation (RPA) in logistics firms has significantly improved order processing efficiency and accuracy by reducing manual and repetitive tasks.¹⁴ Similarly, data analytic-based logistics modelling frameworks have been shown to enhance delivery performance and support better decision-making through real-time data analysis and geographic mapping of supply chain actors.¹⁵ These improvements lead to greater accountability and efficiency in operations. As a result, businesses become more resilient and contribute more effectively to sustainable development. Recent global disruptions have further exposed the vulnerability of supply chains, particularly in emerging economies. A systematic review of COVID-19 impacts revealed significant weaknesses in inventory management, sustainability practices, and strategic risk planning across multiple industries.¹⁶ The growing intersection between sustainable supply chain management and supply chain risk management highlights the need for resilient and robust systems that can withstand environmental and economic uncertainties.¹⁷ In this context, digital transformation can serve as an enabling mechanism to enhance transparency, coordination, and adaptability within supply chains facing institutional and regulatory challenges. Studies have further emphasized that digital innovation and technologies are transforming supply chain structures by improving automation, integration, traceability, and resource optimization. Digital tools such as artificial intelligence, big data analytics, cloud computing, and cyber-physical systems have been shown to enhance operational transparency and promote sustainable development across various industries.¹⁸ These findings reinforce the strategic importance of digital transformation in achieving sustainability goals within heavy industries such as cement manufacturing.

Supply chain activities often create waste and environmental pollution during different stages of production and distribution. The use of digital technologies in supply chain management can reduce these negative impacts by improving coordination and traceability.¹⁹ Many firms are now embracing digital supply chains that integrate technologies such as Radio Frequency Identification (RFID) and the Internet of Things (IoT).²⁰ Through these technologies, companies can achieve greater control over materials and improve communication across different stages of production. Digitization has also transformed how businesses plan and interact with consumers. It enables more accurate demand forecasting, efficient inventory handling, and improved customer service.²¹ In addition, the adoption of Industry 4.0 technologies has been linked to both cost optimization and carbon footprint reduction in supply chain networks, indicating that digital transformation can simultaneously address economic and environmental objectives.²² As consumers increasingly prefer sustainable products with smaller environmental footprints, firms must adapt to meet these expectations. The integration of intelligent manufacturing elements and process automation significantly enhance resource efficiency and minimize waste generation in industrial settings.²³ Such improvements demonstrate how digital transformation supports circular economy objectives by promoting more efficient utilization of materials and reducing environmental impact throughout the production lifecycle. The cement industry, which contributes about 10 percent of global warming through carbon emissions, is under serious pressure to implement sustainability initiatives.²⁴ Digital transformation therefore plays an important role in ensuring that the cement sector adopts more efficient monitoring and management systems to achieve environmental goals.

Previous research has shown that digital transformation in supply chains can significantly improve sustainability performance. Implementing modern and efficient technologies at different stages of cement manufacturing can reduce greenhouse gas emissions by nearly 80 percent.²⁴ Achieving the targets of the Paris Agreement require shared responsibility among governments, industries, and consumers. Despite the potential benefits, limited studies have specifically analyzed the barriers to digitalization for sustainable transformation in the cement industry. This study attempts to fill that gap by focusing on the inhibitors that prevent digital transformation and sustainability improvement in this sector. Contributions from earlier studies on environment and digitization in the cement industry are summarized in Table 1.

Table 1.

Contribution of previous literature on environment and digitization in cement industry.

Serial no.	Authors	Application field	Contribution
1.	Marinelli and Janardhanan²⁴	Cement Industry	Used BWM to rank the barriers encountered in cement industry toward green cement manufacturing in perspective of developing country India
2.	Balsara et al.²⁵	Cement Industry	Used Fuzzy AHP to identify and rank the barriers to emission reduction measures in cement industry of India.
3.	Poudyal and Adhikari¹	Cement Industry	Assessed the feasibility of the re-use of carbon dioxide to produce nano calcium carbonate in cement manufacturing to reduce GHG emissions.
4.	Rodrigues and Joekes²⁶	Cement Industry	Assessed the possible sustainability integration in the cement manufacturing industries.
5.	Ighalo and Adeniyi¹⁰	Cement Industry	Discussed the slow pace of environmental sustainability adoption in the cement industry.
6.	Ada et al.⁴	Cement Industry	Discussed the barriers toward a circular economy in the cement industry.
7.	AlJaber et al.⁵	Building sector	Analyzed the barriers and enablers toward circular economy in the building sector
8.	Karttunen et al.¹¹	Cement Industry	Assessed the environmental innovations in the cement manufacturing industry to address growing concerns of consumers
9.	Uliasz-Bocheńczyk et al.²⁷	Cement industry	Investigated the usage of alternative fuels in cement sector to enhance the circular economy
10.	Okyere et al.²⁸	Cement industry	Explored the possible outcomes of digitalization in the supply chain of cement manufacturing firm and performance enhancement opportunities.

2.2. Sustainability practices and barriers to digital transformation

Cement manufacturing produces large amounts of greenhouse gases and pollutants. Poudyal and Adhikari¹ demonstrated that reusing carbon dioxide to produce calcium carbonate can reduce emissions and support sustainability. It depicts the capability of the manufacturing companies to introduce advanced methods of minimizing environmental footprint contributing to the sustainability aspects of the sector. Similarly, Rodrigues and Joekes²⁶ examined cement chemistry to identify materials that can minimize pollution and encourage recycling. Other researchers have focused on advanced technologies such as the use of alternative fuels, carbon capture and storage (CCS), and energy efficient production systems to reduce environmental impacts.¹⁰

Developed countries have already introduced policies that make sustainability a legal requirement. This has encouraged companies to adopt cleaner production methods and comply with environmental standards. Rehfeldt et al.² discussed this approach in the context of the European Green Deal, which promotes circular and carbon neutral economies. In developing countries, however, the lack of strong regulations and supporting infrastructure limits the implementation of such practices. Digitalization can play a key role in addressing these gaps by enhancing transparency and promoting circular economy practices in the cement sector.²⁸

Several studies have also explored barriers to adopting digital technologies in sustainable manufacturing. Blockchain implementation in supply chains has been found to face technical, organizational, financial, and policy-related challenges, particularly in emerging regions.²⁹ Fuzzy-based approaches such as Fuzzy TOPSIS have been applied to prioritize barriers and drivers influencing digital transformation toward sustainability.³⁰ Similarly, studies on IoT adoption in manufacturing have identified poor infrastructure, high operational costs, and regulatory uncertainty as major driver barriers, using integrated AHP-TOPSIS and ISM techniques to analyze their interdependencies.³¹ Vimal et al.³² identified challenges to applying digital tools in circular economy networks, while Kumar et al.³³ used a hybrid Multiple Criteria Decision Making (MCDM) approach to prioritize strategies for overcoming barriers in Industry 4.0. Dadsena et al.³⁴ analyzed strategies to remove supply chain digitalization barriers in order to achieve Sustainable Development Goals (SDGs). These studies highlight the importance of digital integration in improving supply chain visibility, operational efficiency and stakeholder collaboration.^12,20 Digitalization also supports green supply chain management. Sarkis et al.¹⁹ noted that digital tools can reduce waste generation by improving monitoring, information sharing, and resource management. By minimizing inefficiencies and enhancing transparency, companies can reduce their environmental footprint and strengthen sustainability performance.

The present study focuses on identifying and analyzing the barriers that prevent the cement industry from adopting digital transformation using the Interval Valued Pythagorean Fuzzy DEMATEL method. It aims to develop strategies to mitigate these barriers and promote sustainable digital transformation. Table 2 presents the key barriers identified from the literature.

Table 2.

Identified key barriers to digital transformation for circular transition.

Code	Barriers	Source
F1	Limited lender resources for mitigation financing	Di Filippo et al.,³⁵ Herrera et al.³⁶
F2	Market uncertainty for eco-friendly businesses	Shanks et al.,³⁷ Scrivener et al.³⁸
F3	Lack of environmental commitment among top management	Di Filippo et al.,³⁵ Herrera et al.³⁶
F4	Inconsistent climate regulations from policymakers	Di Filippo et al.,³⁵ Abadie et al.³⁹
F5	Technical expertise deficit in emission reduction	Takacs et al.,⁴⁰ Scrivener et al.³⁸
F6	Insufficient supply chain sustainability incentives	Agrawal et al.,⁴¹ Hossain et al.⁴²
F7	Obstacles to creative circular economy change solutions	Biernacki et al.,⁴³ Smol et al.⁴⁴
F8	Inadequate industrial collaboration	Branca et al.,⁴⁵ Prosman and Wæhrens.⁴⁶
F9	Limited flexibility in reverse logistics	Sonar et al.,⁴⁷ De Souza and D’Agosto.⁴⁸
F10	Insufficient data on subsequent product development phases	Feiz et al.,⁴⁹ Oggioni et al.⁵⁰
F11	Lack of skilled sustainability professionals	Janssens et al.,⁵¹ Clark et al.⁵²
F12	Disputes between sustainable material prioritizing and product quality	Ada et al.,⁴ Amrina and Vilsi.⁵³
F13	Challenges in ensuring recycled material quality	Martin et al.,⁵⁴ Fahim et al.⁵⁵
F14	Inefficient management practice	Nguyen et al.,⁵⁶ Okyere et al.²⁸
F15	Reluctance to invest in recycling	Kandasamy et al.,⁵⁷ Vigren et al.⁵⁸
F16	Reluctance to accept modern technology	K et al.,⁷ Trevisan et al.⁵⁹
F17	Financial barriers to digital technology use	Trevisan et al.,⁵⁹ Osei-Tutu et al.⁶⁰

Bangladesh has a capital-constrained industrial environment, where firms often give more priority to short-term profits over long-term transformation. These financial and market-related barriers significantly obstruct digitalization efforts as digital infrastructure requires significant capital and long payback periods. Limited lender resources for mitigation financing (F1) restrict access to green loans required for digital system integration.^35,36 Market uncertainty for eco-friendly businesses (F2) makes digital traceability and circular platforms seem like a less profitable investment.^37,38 Reluctance to invest in recycling (F15) makes digital monitoring of reverse logistics flows difficult,^57,58 while general financial barriers to digital technology use (F17) restrict procurement of advanced software, data platforms, and automation tools.^59,60

In emerging economies like Bangladesh, it is tough to enforce rules, and policies are not always stable. This lack of stable regulatory enforcement or incentive-based policies makes firms reluctant to adopt digital systems that support circular transition. Inconsistent climate regulations (F4) reduce pressure to implement digital carbon accounting and compliance tracking systems.^35,39 Whereas, insufficient supply chain sustainability incentives (F6) weaken motivation to digitize coordination among suppliers, distributors, and recycling partners.^41,42

Hierarchical organizational cultures, generational leadership gaps, and resistance to strategic change are common in traditional manufacturing sectors of developing countries. It weakens the managerial commitment to go for digitally enabled sustainability initiatives. Lack of environmental commitment among top management (F3) prevents company to prioritize digital transformation initiatives.^35,36 Inefficient management practices (F14) make it harder for managers to make data-driven decisions and integrate multiple departments, which are all needed for implementing a digitalized system.^28,56 Reluctance to accept modern technology (F16) is often influenced by generational leadership gaps and the tendency to avoid taking risk.^7,59

Bangladesh often face shortages of digitally skilled industrial professionals and limited technical training infrastructure. These technical and human capital barriers hinder the adoption of digital systems. Technical expertise deficits in emission reduction (F5) and lack of skilled sustainability professionals (F11) reduce firms’ ability to use advanced digital monitoring tools and analytics platforms to keep their emission in check.^38,40,51,52 Insufficient data on subsequent product development phases (F10) shows that digital record-keeping practices are weak. This makes it hard to trace the lifecycle of a product, which is necessary for circular economy modelling.^49,50

In emerging economy supply chains are often characterized by fragmentation, informal coordination practices, and weak inter-firm data integration and operational inflexibilities. This significantly constrains the data-sharing ecosystem essential for integrated digital supply chains. Limited flexibility in reverse logistics (F9) makes it harder to set up digitally monitored systems for material recovery.^47,48 Disputes between sustainable material prioritization and product quality (F12) creates uncertainty over whether recycled inputs will compromise product performance.^4,53 This reduces managerial willingness to invest in digital traceability and monitoring systems. Due to inconsistent recycled material quality, challenges in ensuring recycled material quality (F13) undermines reliable data standardization, making integration into digital quality-control, ERP, and lifecycle monitoring systems technically risky and difficult.^54,55 Obstacles to creative circular economy solutions (F7) reflect limited innovation capacity, which constrains the development of digitally enabled circular business models.^43,44

Based on the reviewed literature, digital transformation in the cement industry can be conceptualized as a multi-dimensional process involving technological integration, organizational change, financial investment, regulatory alignment, and supply chain coordination. The literature review shows that while sustainability and circular economy practices in the cement industry have been widely studied, research specifically linking digital transformation to these goals is still very limited. Previous studies have examined environmental innovations and policy frameworks, but there is a research gap that explores the combined role of digital technologies and circular economy principles and a structured causal analysis of the barriers that hinder this transformation in cement manufacturing. This lack of research is even more visible in emerging economies such as Bangladesh, where digital transformation faces unique institutional, financial, and cultural challenges. Therefore, this study contributes by identifying the barriers that restrict digital transformation in the cement sector and by applying an IVPF-DEMATEL framework to prioritize them. The review confirms the need for a comprehensive model that integrates digital transformation, sustainability, and circular economy objectives for the cement industry in developing contexts.

3. Research methodology

3.1. Collection of data and survey design

This study on identifying barriers to digital transformation adoption in the cement manufacturing industry, particularly in developing economies, began with a systematic review of relevant academic literature. The search was conducted using major scholarly databases such as Scopus, Web of Science, and Google Scholar. The keywords used included “Digital transformation,” “Cement industry,” “Adoption barriers,” “Digital servitization,” and “Emerging economies.” To ensure both relevance and recentness, the review was limited to peer reviewed journal articles published between 2015 and 2025, with a few earlier studies included for conceptual reinforcement. This approach followed the methodological framework proposed by Kumar et al.⁶¹ for industrial literature synthesis under uncertain conditions. The process initially identified seventeen potential barriers, which were later validated by industry experts to ensure their applicability to the cement sector.

An expert committee comprising twelve specialists was deliberately selected for validation and evaluation of the barriers. The selection followed the expert choice criteria suggested by Saaty⁶² for decision making research. Each expert had at least ten years of professional experience in digital transformation, sustainable manufacturing, or supply chain management within the cement industry. The expert group represented diverse professional backgrounds, including academia, cement manufacturing, and consulting firms, thus providing a balanced mix of practical and theoretical perspectives. The demographic characteristics of the participating experts are presented in Table 3.

Table 3.

Demographic profiles of participating experts.

Expert	Institution type	Area of expertise	Tenure (Years)	Position
E1	Cement Manufacturing Firm	Digital Transformation	15	Chief Technology Officer
E2	Cement Manufacturing Firm	Sustainability in Manufacturing	12	Sustainability Manager
E3	Cement Manufacturing Firm	Supply Chain Management	14	Supply Chain Director
E4	Academic Institution	Industrial Digitalization	18	Professor
E5	Academic Institution	Sustainable Manufacturing	16	Associate Professor
E6	Consulting Firm	Digital Transformation Consulting	13	Senior Consultant
E7	Cement Manufacturing Firm	Operations Management	11	Operations Manager
E8	Academic Institution	Supply Chain Sustainability	15	Professor
E9	Consulting Firm	Environmental Management	12	Sustainability Consultant
E10	Cement Manufacturing Firm	Process Engineering	14	Process Engineer
E11	Academic Institution	Digital Servitization	17	Research Director
E12	Consulting Firm	Technology Adoption Strategies	10	Technology Consultant

Data collection was conducted through a structured questionnaire designed to obtain expert judgments on the relationships between the identified barriers. The questionnaire included clear definitions of each barrier and specific instructions to minimize ambiguity. Experts provided pairwise comparisons to assess the influence of one barrier on another, using a linguistic scale consisting of five terms: “No influence” (N), “Very low influence” (VL), “Low influence” (L), “High influence” (H), and “Very high influence” (VH) as listed in the following Table 4. These linguistic responses were then converted into Interval Valued Pythagorean Fuzzy (IVPF) numbers. The IVPF representation allows for the consideration of uncertainty in expert judgments by incorporating both membership and non-membership degrees within specified intervals. This approach enables a more realistic analysis of qualitative assessments in complex decision-making environments.⁶³

Table 4.

IVPF-DEMATEL linguistic scale.

Linguistic	Abbreviation	μL	μU	vL	vU	Crisp
No influence	N	0.000	0.000	1.000	1.000	0.000
Very low influence	VL	0.120	0.250	0.500	0.780	0.314
Low influence	L	0.210	0.340	0.560	0.690	0.366
High influence	H	0.560	0.690	0.210	0.340	0.634
Very high influence	VH	0.650	0.780	0.120	0.250	0.711

The pairwise comparisons obtained from the experts were compiled into a direct relation matrix, which served as the primary input for the IVPF DEMATEL analysis. The use of linguistic scales and fuzzy modeling ensured the capture of both qualitative insights and quantitative consistency.⁶⁴ This combination made it possible to evaluate not only the direct effects among the barriers but also the indirect and interdependent relationships that exist within the system.

3.2. Justification and context for using the hybrid IVPF-DEMATEL framework

The selection of IVPF-DEMATEL framework is justified by its ability to handle uncertainty and complexity in expert-based evaluations.⁶³ The adoption of digital transformation in the cement industry involves numerous interrelated barriers that are difficult to measure precisely. Conventional multi criteria decision making methods, such as the Analytic Hierarchy Process (AHP) or basic ranking techniques, often struggle to model the dependencies and ambiguities present in such problems.⁶² The hybrid IVPF DEMATEL method addresses these limitations by combining the flexibility of fuzzy set theory with the causal analysis capabilities of DEMATEL.

The DEMATEL technique is particularly effective in revealing cause and effect relationships among multiple factors within complex systems.⁶⁵ It converts qualitative expert opinions into quantitative matrices that identify both direct and indirect influences among variables. In the context of the cement industry, where barriers such as resistance to technological change, lack of environmental commitment, and financial limitations interact dynamically, DEMATEL provides a systematic way to uncover the underlying structure of these relationships.⁶¹

However, classical DEMATEL requires precise numerical data, which may not always be available in developing economies where expert opinions vary widely.⁶⁶ The integration of Interval Valued Pythagorean Fuzzy Sets (IVPFS) overcomes this issue by introducing interval-based membership and non-membership values. This allows experts to express hesitation or uncertainty in their judgments, thus making the evaluation more flexible and realistic.⁶⁷ For example, when assessing how the lack of environmental commitment among top management influences reluctance to invest in recycling, an expert may specify a range of possible influence levels (membership [0.6, 0.8], non-membership [0.1, 0.3]) rather than a single fixed value.

This hybrid approach is particularly suitable for analyzing the barriers to digital transformation in the cement industry, which operates under high capital intensity, regulatory diversity, and varied technological maturity across emerging economies.⁶⁸ By using IVPF DEMATEL, the study can map both the prominence and causal strength of barriers, distinguishing those that are root causes from those that are effects.⁶³ The framework not only provides numerical insights but also visual representations of relationships, allowing policymakers and industry leaders to focus on the most critical factors driving or hindering digital adoption.

In summary, the IVPF DEMATEL framework offers a robust and structured approach for analyzing complex, uncertain, and interdependent barriers. It ensures a comprehensive understanding of how organizational, financial, and technological factors interact in the process of digital transformation. This makes it an appropriate and effective tool for supporting evidence-based decision making in the cement industry of emerging economies.

3.3. Evaluation of the barriers through the IVPF-DEMATEL framework

3.3.1. Fundamentals of interval-valued pythagorean fuzzy set theory

In multi-expert decision environments, uncertainty and imprecision are common. Numerous frameworks have been developed to express such vagueness in expert judgments. The earliest and most influential contribution came from Zadeh, who introduced the concept of fuzzy sets (FS).⁶⁹ In a fuzzy set, each element is associated with a membership value (μ) within [0, 1], reflecting the degree to which it belongs to a given set.⁷⁰ This approach extends classical set theory by allowing partial inclusion between absolute membership and total exclusion.⁷¹ In fuzzy sets, the membership function substitutes the characteristic function used in crisp sets and indicates the degree to which an element belongs to a particular class.^72–75

Despite its usefulness, the traditional fuzzy model does not explicitly consider non-membership or hesitation. To overcome this limitation, Atanassov⁷⁶ proposed the intuitionistic fuzzy set (IFS),⁷⁷ which incorporates both membership (μ) and non-membership degrees (ν)⁷⁸ together with a hesitation parameter (π).⁷⁹ The conditions ν + μ ≤ 1 and π + ν + μ=1 must be satisfied for these three components.⁸⁰ IFS therefore captures an additional zone of uncertainty, representing cases where decision makers are not completely confident about inclusion or exclusion. Later, developments extended this idea, but in some contexts μ + ν ≥ 1 can hold, which is not covered by the IFS framework.^81–83 Yager⁶⁷ addressed this gap by developing the Pythagorean Fuzzy Set (PFS), which allows the squared sum μ² + ν² ≤ 1. It improves the properties of intuitionistic fuzzy sets and provide a wider scope for representing uncertainty in decision-making problems.^84–87 Therefore, PFS emerges as a potential approach⁸⁸ to address the adoption barriers for digital transformation within the cement industry.

Zhang and Xu⁸⁹ further generalized the model to the Interval-Valued Pythagorean Fuzzy Set (IVPFS) to better capture uncertainty in human reasoning.⁹⁰ IVPFS represents membership and non-membership degrees as closed intervals [μL, μU] and [νL, νU], respectively. This enables decision makers to express their opinions as ranges instead of precise numbers.⁹¹ Thus, making it better suited to capture ambiguity in decision making situations and serve as a more applicable generalization of FS, IFS, and PFS.⁹² Although this reduces precision, it retains key informational content and provides a more practical framework for real-world decision problems.⁹³ That is why this model was used to capture the ambiguity in expert assessments of barriers that hinder the adoption of digitalization in the context of cement manufacturing. The detailed mathematical formulations used in this study are presented in Appendix A.

3.3.2. Application of the DEMATEL method

The DEMATEL approach is applied to analyze the cause-and-effect structure among the identified challenges. It is particularly suitable for complex decision-making scenarios.⁶⁵ This method involves a panel of experts E = {E₁, E₂, …, E_m} who evaluate the influence among factors F = {F₁, F₂, …, F_n} on a predefined scale: 0 (no influence), 1 (very low influence), 2 (low influence), 3 (high influence), and 4 (very high influence). Each expert provides a direct influence matrix (Z_k) representing their assessments, with the diagonal elements set to zero, indicating no self-influence.⁶⁴ The steps of the DEMATEL method are given in below.

Step 1: Direct Influence Matrix (Z):

The direct influence matrix is calculated as the average of all experts' evaluations:

Z = \frac{1}{m} \sum_{k = 1}^{m} z_{k}

(1)

Step 2: Normalized Direct-Influence Matrix (X):

The direct influence matrix is normalized to ensure all elements fall within a manageable range:

X = \frac{Z}{\max (\max (\sum_{i = 1}^{n} z_{i j}), \max (\sum_{j = 1}^{n} z_{i j}))}

(2)

Step 3: Total Influence Matrix (T):

The total influence matrix is computed to capture both direct and indirect influences among factors:

T = X {(I - X)}^{- 1}

(3)

Step 4: Influential Relation Map (IRM):

The D (sum of rows) and R (sum of columns) values are derived from the total influence matrix to identify each factor’s prominence (D+R) and its nature as a cause or effect (D−R):

D = \sum_{j = 1}^{n} t_{ij}, R = \sum_{i = 1}^{n} t_{ij}

(4)

The D+R, known as “Prominence,” reflects the overall significance of a factor in the system, whereas D−R, called “Relation,” identifies whether a factor primarily acts as a cause or an effect. This structured methodology enables a clear visualization of interdependencies, aiding decision-makers in prioritizing and addressing critical factors systematically.

4. Results and findings

The results of the IVPF-DEMATEL analysis are presented in this section. Detailed numerical values and matrix derivations are included in the Appendix B (Tables B1–B4). The defuzzified influence relation matrix (IRM) is shown in Table 5. Tables 6 and 7 summarize the computed prominence (D + R) and relation (D – R) values respectively, which are used to determine the overall importance and directional influence of each barrier.

Table 5.

Defuzzified IRM.

Code	Influencing factors	D	R
F1	Limited lender resources for mitigation financing	2.356	2.410
F2	Market uncertainty for eco-friendly businesses	2.580	2.560
F3	Lack of environmental commitment among top management	3.787	3.881
F4	Inconsistent climate regulations from policymakers	3.114	3.127
F5	Technical expertise deficit in emission reduction	2.768	2.779
F6	Insufficient supply chain sustainability incentives	3.415	3.403
F7	Obstacles to creative circular economy change solutions	1.775	1.765
F8	Inadequate industrial collaboration	2.107	2.280
F9	Limited flexibility in reverse logistics	3.933	3.875
F10	Insufficient data on subsequent product development phases	3.303	3.321
F11	Lack of skilled sustainability professionals	2.976	2.997
F12	Disputes between sustainable material prioritizing and product quality	3.530	3.826
F13	Challenges in ensuring recycled material quality	3.184	3.171
F14	Inefficient management practice	2.406	2.265
F15	Reluctance to invest in recycling	3.852	3.497
F16	Reluctance to accept modern technology	2.347	2.329
F17	Financial barriers to digital technology use	2.047	1.995

Table 6.

The barriers with prominence ranking.

Barrier code	Influencing factors	(D + R) value	Prominence ranking
F9	Limited flexibility in reverse logistics	7.809	1
F3	Lack of environmental commitment among top management	7.669	2
F12	Disputes between sustainable material prioritizing and product quality	7.356	3
F15	Reluctance to invest in recycling	7.349	4
F6	Insufficient supply chain sustainability incentives	6.817	5
F10	Insufficient data on subsequent product development phases	6.624	6
F13	Challenges in ensuring recycled material quality	6.355	7
F4	Inconsistent climate regulations from policymakers	6.241	8
F11	Lack of skilled sustainability professionals	5.974	9
F5	Technical expertise deficit in emission reduction	5.547	10
F2	Market uncertainty for eco-friendly businesses	5.139	11
F1	Limited lender resources for mitigation financing	4.766	12
F16	Reluctance to accept modern technology	4.676	13
F14	Inefficient management practice	4.672	14
F8	Inadequate industrial collaboration	4.387	15
F17	Financial barriers to digital technology use	4.042	16
F7	Obstacles to creative circular economy change solutions	3.540	17

Table 7.

The barriers with causal ranking.

Barrier code	Influencing factors	(D - R) value	Causal ranking	Group
F15	Reluctance to invest in recycling	0.356	1	Cause
F14	Inefficient management practice	0.141	2	Cause
F9	Limited flexibility in reverse logistics	0.058	3	Cause
F17	Financial barriers to digital technology use	0.052	4	Cause
F2	Market uncertainty for eco-friendly businesses	0.020	5	Cause
F16	Reluctance to accept modern technology	0.017	6	Cause
F13	Challenges in ensuring recycled material quality	0.013	7	Cause
F6	Insufficient supply chain sustainability incentives	0.012	8	Cause
F7	Obstacles to creative circular economy change solutions	0.010	9	Cause
F5	Technical expertise deficit in emission reduction	-0.012	10	Effect
F4	Inconsistent climate regulations from policymakers	-0.013	11	Effect
F10	Insufficient data on subsequent product development phases	-0.018	12	Effect
F11	Lack of skilled sustainability professionals	-0.021	13	Effect
F1	Limited lender resources for mitigation financing	-0.055	14	Effect
F3	Lack of environmental commitment among top management	-0.094	15	Effect
F8	Inadequate industrial collaboration	-0.172	16	Effect
F12	Disputes between sustainable material prioritizing and product quality	-0.295	17	Effect

4.1. Overview of the analytical results

As presented in Table 5, the D + R and D – R scores were derived for all seventeen identified barriers. These indices provide insight into the magnitude and nature of interactions among the barriers. The D + R value measures a barrier’s overall prominence, while D – R distinguishes between the barriers that exert influence (cause) and those that are more responsive (effect).

According to Table 6, “limited flexibility in reverse logistics” (F9) and “lack of environmental commitment among top management” (F3) exhibit the highest prominence values, indicating that they play major roles in influencing the network of interdependent barriers. Conversely, barriers such as “obstacles to creative circular economy change solutions” (F7) and “financial barriers to digital technology use” (F17) have lower prominence, suggesting relatively limited systemic importance.

From Table 7, positive D – R values signify cause-type barriers, meaning they drive other constraints in the system. Negative D – R values denote effect-type barriers, which are largely outcomes of other influencing factors. “Reluctance to invest in recycling” (F15) and “inefficient management practice” (F14) emerge as dominant causal factors, while “disputes between sustainable material prioritizing and product quality” (F12) and “inadequate industrial collaboration” (F8) appear as major effect barriers.

4.2. Causal mapping and classification of barriers

Figure 1 displays the distribution of the barriers based on their D + R and D – R values. The horizontal axis (D + R) represents overall prominence, showing how strongly a barrier is connected within the system. The vertical axis (D – R) shows the direction of influence, distinguishing cause-type from effect-type barriers.

Figure 1.

Causal network of barriers to digital transformation.

Barriers located in the upper region of the graph (positive D – R) act as initiators or driving forces, exerting direct or indirect influence on others. Those in the lower region (negative D – R) behave as dependent or responsive elements, being more affected by external conditions. This visual analysis makes it clear that addressing cause-type barriers can lead to improvement across the network since changes in these areas cascade throughout the system.

For example, improving managerial efficiency (F14) and encouraging investment in recycling technologies (F15) are likely to create ripple effects that reduce many downstream difficulties such as poor collaboration (F8) and quality disputes in recycled materials (F12). The figure therefore highlights the directional nature of interactions among the barriers and provides a strategic foundation for prioritizing interventions.

Figure 2 illustrates the distribution of barriers across four quadrants according to their prominence (D + R) and causal influence (D – R). This graphical mapping helps to distinguish which barriers act as strong initiators, which are dependent outcomes, and which hold limited roles within the network. It shows that the “Core Driving” and “Potential Enabling” barriers occupy the upper quadrants, forming the “cause group,” while “Dependent” and “Peripheral” barriers form the “effect group.” Such visual mapping aids policymakers and industrial managers in identifying leverage points where strategic action yields the greatest overall benefit.

Figure 2.

Categorization of barriers by prominence and causal influence.

Core Driving Barriers – These barriers, located in the upper-right quadrant (F15, F9, F6, F13), demonstrate both high prominence and strong causal influence. They serve as the primary forces shaping the digital transformation landscape. F15 (reluctance to invest in recycling) appears in the extreme top-right position, highlighting it as the most critical factor, followed closely by F9 (limited flexibility in reverse logistics). Together, these barriers represent pivotal leverage points that policymakers should prioritize to trigger widespread improvements across the system.

Potential Enabling Barriers – Found in the upper-left quadrant (F14, F17, F7, F16, F2), these barriers show high causal strength but relatively low prominence. They exert influence on others but do not occupy central positions in the overall network. F14 (inefficient management practice) and F17 (financial barriers to digital technology use) initiate systemic challenges even though their direct visibility in the system is moderate.

Dependent Barriers – The lower-right quadrant (F12, F3, F10, F4, F11) represents barriers with high prominence but low causal influence. These are resultant or outcome barriers that become significant because they are affected by the actions of the core and enabling barriers. F12 (disputes between sustainable material prioritizing and product quality) and F3 (lack of environmental commitment among top management) are prominent examples, reflecting the downstream effects of upstream managerial and financial issues.

Peripheral Barriers – Barriers in the lower-left quadrant (F8, F1, F5) possess both low prominence and low causal strength. They function as marginal elements in the system, exerting limited influence while also being weakly connected to the major drivers. Although they have lesser strategic significance, continuous neglect could still hinder incremental progress in digital transformation.

Figure 3 presents the two-dimensional relationship between the prominence and causal rankings of the seventeen barriers. The horizontal axis indicates the prominence ranking, representing the overall importance of each barrier, while the vertical axis shows the causal ranking, indicating the degree of influence exerted on other factors. In this representation, lower values correspond to higher rank.

Figure 3.

Comparative ranking of barriers by prominence and causality.

Barriers F9 (Limited flexibility in reverse logistics) and F15 (Reluctance to invest in recycling) appear in the lower-left corner, confirming their position as the most influential and significant challenges. Their high standing in both prominence and causal rankings indicates that they are key driving barriers that strongly shape the entire network.

In contrast, F8 (Inadequate industrial collaboration) and F1 (Limited lender resources for mitigation financing) occupy the upper-right corner, representing low-ranking barriers in both dimensions. These factors have comparatively weaker influence and importance, suggesting that they are outcomes of other upstream issues rather than primary causes.

The lower-right quadrant, where F14 (Inefficient management practice) and F17 (Financial barriers to digital technology use) are located, corresponds to barriers that demonstrate high causal influence but low overall prominence. These act as specific or isolated drivers whose effects are strong but limited to particular areas of the system.

Conversely, F3 (Lack of environmental commitment among top management) and F12 (Disputes between sustainable material prioritizing and product quality) lie in the upper-left quadrant, showing high prominence but low causal strength. These barriers are highly visible within the system yet behave more as outcomes influenced by the core financial and managerial constraints.

5. Discussion

This study applied the Interval-Valued Pythagorean Fuzzy DEMATEL (IVPF-DEMATEL) method to investigate the barriers hindering digital transformation toward circular transition in the cement industry of an emerging economy. From the analysis of seventeen identified barriers, the results reveal that limited flexibility in reverse logistics (F9) and lack of environmental commitment among top management (F3) emerged as the most prominent inhibitors. In terms of causality, reluctance to invest in recycling (F15) and inefficient management practice (F14) were identified as critical root causes. The emergence of inefficient management practice as a key causal barrier provides further evidence that digital transformation efforts often falter not due to lack of tools, but due to systemic mismanagement of change. In Bangladesh’s cement firms, decision‐making authority is often centralized among senior managers or family‐owners, creating hierarchical cultures where innovation and risk-taking are discouraged. These managers may belong to an older generation trained under less dynamic market conditions, and thus prioritize proven procedures over novel approaches. Digital transformation requires organizational restructuring and workforce reskilling. But senior managers often prioritize short-term production stability and cost control over long-term sustainability investments.⁹⁴ Such conditions create resistance to experimentation with new technologies, even when there are potential environmental and efficiency benefits. Similar managerial inertia has been observed in cement firms operating in emerging economies, where leadership hesitation and limited strategic alignment often delay the implementation of environmentally oriented innovations.⁹⁵ These results echo insights from Rukuni et al.,⁹⁶ who found that managerial reluctance limits green process adoption in South African cement firms. These findings underline the complex, interconnected nature of digital transformation barriers. It shows how organizational leadership, operational flexibility, and systemic inefficiencies interact to slow sustainability-oriented transformation. The prominence of F9 and F3 suggests that both structural rigidity in logistics and insufficient managerial prioritization of sustainability remain dominant constraints in the cement sector. Reverse logistics in the cement sector is inherently complex because materials such as demolition waste, clinker substitutes, and industrial by-products must be collected, sorted, and reintegrated into production streams. In many emerging economies, supply chains, logistics networks were historically designed for one-directional product distribution rather than circular material flows.⁹⁷ This structural rigidity limits the ability of firms to implement digitally coordinated reverse logistics systems, which are essential for monitoring recycled material quality and optimizing circular supply chains. Additionally, the lack of environmental commitment among top management (F3) further constrains digital transformation initiatives, as strategic investment in sustainability-oriented digital systems often depends on leadership prioritization and long-term vision. In many emerging economies, managerial focus tends to remain on short-term operational efficiency rather than integrating digital tools that enable circular and environmentally responsible supply chains.⁹⁴

The results also highlight that barriers, such as disputes over sustainable materials (F12) and inadequate industrial collaboration (F8), are effect-type factors. These factors are heavily dependent on upstream managerial and financial causes. This hierarchy indicates that addressing root-level inefficiencies, particularly weak management systems and investment aversion could produce much improvements across the supply chain. Overall, the analysis provides a systematic map of how economic, regulatory, and organizational factors interlink to impede the digital transformation of the cement industry. The IVPF-DEMATEL framework proved particularly valuable in this regard, allowing the visualization of interdependencies and the identification of leverage points within a web of uncertainties, consistent with earlier methodological applications in industrial research.⁹⁸

This research contributes to the emerging body of work on digital transformation and sustainability transitions by offering a structured understanding of how barriers interact. While earlier studies in the cement sector largely emphasized circular economy barriers^4,5 or green manufacturing challenges,²⁴ they have primarily treated these barriers in isolation. They also did not explicitly address digital integration in the context of emerging economies. By extending the literature with a decision-making framework that reveals causal-effect relationships, this study fills a critical gap and reveals how leadership deficiencies and rigid logistics structures extend financial, technological, and policy challenges.

Furthermore, the findings align with broader debates on Industry 4.0 adoption barriers^32,33,99 particularly in sectors characterized by low technological maturity. While reluctance to accept modern technology (F16) and financial barriers (F17) continue to appear in the causal layer, their relatively lower ranking here underscores that organizational reluctance and management inefficiency exert stronger influence than technological hesitancy alone. This insight reinforces the argument made by Zada et al.¹⁰⁰ that digital sustainability challenges are less about technological availability and more about aligning organizational structures and leadership intent with sustainability objectives.

The findings resonate with previous work emphasizing the slow uptake of sustainability in the cement sector^10,26 but extend the analysis by incorporating digitalization as a central enabler. Unlike studies from developed context,² where regulatory enforcement and technological infrastructure are relatively robust, the emerging economy perspective here highlights institutional gaps such as inconsistent climate regulations (F4) and lack of skilled professionals (F11).

The study’s differentiation between cause and effect barriers strengthens theoretical understanding of inter-barrier dependency. The identification of F15 (reluctance to invest in recycling) as the strongest causal factor is consistent with prior research emphasizing that proper economic incentives and government policies can encourage circular reinvestment in industries.¹⁰¹ In Bangladesh’s context, recycling processes often lack proven business models.¹⁰² The reluctance to invest in recycling is often linked to uncertainty regarding economic returns. There are also the perceived operational risks of adding recycled materials into existing production systems.¹⁰³ Investments in cement manufacturing company are typically directed toward maintaining kiln efficiency and production capacity. As a result, digitalized circular initiatives such as waste material recovery or digital tracking of recycled inputs are frequently viewed as secondary priorities. Without clear economic incentives or reliable regulations, managers may postpone such investments. Thus, the development of digital infrastructures required for circular supply chains is hindered. Moreover, the presence of F8 (inadequate industrial collaboration) among effect-type barriers suggests that fostering sector-wide alliances could mitigate downstream issues and support digital data-sharing ecosystems. Importantly, the findings suggest that the success of digital transformation in resource-intensive industries is closely tied to organizational culture and leadership commitment. Even when digital tools are available, their effective deployment depends on managerial willingness to adopt data-driven decision-making and integrate sustainability into strategic planning. Without such leadership alignment, digital transformation initiatives may remain fragmented or limited to isolated technological upgrades rather than enabling systemic circular transition. Theoretically, the integration of IVPF-DEMATEL underlines its robustness as a decision-support tool capable of quantifying causal intensity and managing expert uncertainty,¹⁰⁴ echoing methodological advances in fuzzy multi-criteria analysis for industrial decision-making.

5.1. Managerial implications for industry

For practitioners, the study underscores the necessity of top management engagement in driving digital transformation. Without explicit environmental commitment from top management (F3), investments in digital tools may remain fragmented and fail to achieve systemic sustainability gains. Cement firms must prioritize data-driven decision-making by developing systems to capture, track, and share product lifecycle data, which in turn supports recycling (F15) and reverse logistics (F9) efficiency. The identification of inefficient management practice (F14) as a key causal factor suggests that improving managerial competency, transparency, and data-driven decision-making can have ripple effects across other dependent barriers. For managers in the cement industry, this implies that digital transformation initiatives should be led at the executive level. It should be embedded into long-term strategic planning rather than being treated as isolated technology projects. Firms should establish cross-functional sustainability teams, and adopt performance indicators that link environmental targets with operational decision-making.

Furthermore, addressing disputes between sustainable materials and product quality (F12) requires joint innovation between R&D teams and digital monitoring systems that can ensure compliance without compromising performance standards. Capacity building through training sustainability professionals (F11) and enhancing cross-industry collaborations (F8) could help mitigate effect-type barriers, enabling a more holistic adoption of digital transformation.

5.2. Policy recommendations

Policymakers play a central role in addressing the causal barriers identified. The persistence of reluctance to invest in recycling (F15) and inefficient management practice (F14) points to the need for incentive-based policies and capacity-building programs targeting managerial performance and investment behavior. Governments could introduce green financing mechanisms, tax incentives for circular investments, and performance-based subsidies to reduce the perceived risk of investing in recycling technologies and digital monitoring systems. Finally, supporting industrial alliances could bridge the collaboration gaps (F8) revealed in the study, facilitating shared knowledge platforms and joint technology pilots for circular manufacturing.

5.3. Contextual insights for emerging economies

The results emphasize that the barriers to digital transformation in emerging economies differ substantially from those in developed contexts. While technological reluctance (F16) and financial limitations (F17) are common, institutional fragility, cultural conservatism, and managerial inefficiency (F14) amplify their effects in Bangladesh and similar economies. The causal dominance of reluctance to invest in recycling (F15) reflects not only financial caution but also the absence of systemic incentives and infrastructure to make recycling economically viable. These contextual insights are crucial because they caution against transplanting digital transition models from developed economies into emerging ones without adaptation. Instead, industry and policymakers must co-develop strategies sensitive to local realities, including financing constraints, data gaps, and limited stakeholder alignment. In summary, digital transformation for sustainability in the cement industry hinges less on technical capability and more on managerial intent, institutional design, and industrial collaboration. Strengthening these dimensions can accelerate the transition toward digitally enabled circular operations in resource-intensive industries under uncertainty.

5.4. Global implications of the findings

Although this study focuses on Bangladesh as a representative emerging economy, the insights have broader relevance for the global cement industry and other resource-intensive sectors undergoing digital and circular transitions. Many cement-producing countries across Asia, Africa, and Latin America face similar institutional and managerial constraints, including limited digital maturity, fragmented supply chains, and weak incentives for recycling investments.^95,96 The identification of managerial inefficiency and investment reluctance as primary causal barriers suggests that digital transformation challenges are not purely technological but organizational in nature. This finding implies that global sustainability initiatives in heavy industries must place greater emphasis on managerial capability development, leadership commitment, and strategic alignment with circular economy goals. Consequently, multinational cement producers, policymakers, and development agencies can utilize the barrier hierarchy identified in this study as a diagnostic framework to prioritize managerial reform, recycling investment incentives, and digital supply chain coordination when designing global sustainability strategies.

6. Conclusion

This study investigated the barriers to digital transformation that enable circular transition in the cement industry within an emerging economy context. Using the Interval-Valued Pythagorean Fuzzy DEMATEL (IVPF-DEMATEL) method, seventeen barriers were identified and their causal relationships were analyzed to distinguish between causal and effect-type factors. The analysis revealed that reluctance to invest in recycling (F15) and inefficient management practice (F14) act as pivotal causal barriers. In contrast, limited flexibility in reverse logistics (F9) and lack of environmental commitment among top management (F3), emerged as the most prominent barriers. These results suggest that challenges to digital transformation in the cement industry are not purely technological but are strongly rooted in managerial practices, strategic priorities, and investment decisions.

The findings offer two key contributions. First, they extend the limited literature on digital transformation in heavy industries by providing a structured, causal-effect perspective tailored to emerging economies. Second, they provide practical guidance for both industry managers and policymakers: firms must prioritize operational adaptability, managerial alignment with sustainability goals, and integration of recycling investments, while governments should establish consistent regulatory frameworks, targeted financial incentives, and collaborative platforms to accelerate digital and circular transitions. Beyond the Bangladesh context, these findings provide guidance for cement producers and policymakers in other emerging economies facing similar sustainability and digitalization challenges, highlighting the importance of managerial leadership, circular investment strategies, and digital supply chain integration in accelerating global low-carbon industrial transformation.

6.1. Limitations

Although the study provides a robust analysis, some limitations should be noted. The reliance on expert opinion, while carefully validated, restricts the findings to the perceptions of a relatively small sample from Bangladesh. Broader surveys or cross-country comparisons would enhance generalizability. Additionally, while IVPF-DEMATEL is effective in modeling interdependencies, it does not capture dynamic changes over time, leaving scope for longitudinal studies to assess how barriers evolve as digital adoption progresses.

6.2. Directions for future research

Future research could extend this study by conducting comparative analyses across multiple emerging economies, exploring whether similar causal patterns hold in different institutional contexts. Another promising avenue is integrating IVPF-DEMATEL with other multi-criteria decision-making methods, such as Analytic Network Process (ANP) or Best-Worst Method (BWM), to triangulate findings. Moreover, as digital adoption advances, empirical investigations into actual firm-level implementation outcomes would provide practical validation of the barriers identified here. Finally, exploring the intersection of digital transformation with renewable energy adoption in cement could broaden the sustainability lens.

Supplemental material

Supplemental material - Barriers to digital transformation for circular transition in the cement industry: An emerging economy perspective

Supplemental material for Barriers to digital transformation for circular transition in the cement industry: An emerging economy perspective by Rafid Ahmed Chowdhury, Golam Fahim, A. I. M. Johurul Islam, M. Nafis Ahsan in International Journal of Engineering Business Management

Footnotes

ORCID iD

Rafid Ahmed Chowdhury

Ethical considerations

This study did not involve human participants, human data, or human tissue. Formal ethics approval was therefore not required.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data supporting the findings of this study are available within the article and the appendix.*

Supplemental material

Supplemental material for this article is available online.

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