Purpose This study evaluates, from a business process management (BPM) perspective, four reverse logistics (RL) strategies (Lockers, Click & Collect, Microhubs and 3PL) once product returns are authorized. It addresses the critical first-stage decision – home collection vs designated drop-off – while explicitly analyzing the detrimental impact of failed collection attempts due to customer absence on urban logistics efficiency, aiming to enhance the business performance of e-commerce retailers and logistics providers. Design/methodology/approach A decision support framework is developed, applying the technique for order preference by similarity to ideal solution to assess each strategy and a simulation of 1,000 product return scenarios is conducted. The methodology incorporates a robust sensitivity analysis modeling varying rates of failed first-time collections, quantifying their effect on cost, cycle time, CO2 emissions and expected customer utility. Findings Baseline results identify Urban Microhubs as the most balanced strategy. However, sensitivity analysis reveals that as failed collections increase, the efficiency of attended strategies (3PL and Urban Microhubs) degrades significantly due to re-attempt costs. This shifts the strategic preference toward unattended strategies like lockers. Originality/value The study offers original value by integrating operational, environmental and customer-focused metrics into a unified framework for evaluating RL scenarios. Its multidimensional comparison of the four strategies provides novel insights that advance theory and guide the design of more efficient and sustainable return strategies, enabling e-commerce and logistics operators to adopt differentiated policy profiles (cost-driven or green-driven). Ultimately, the primary value of this research resides in providing a structured methodology to analyze complex operational scenarios. Additionally, the explicit modeling of failed collections provides novel insights that advance BPM theory, empowering context-specific managerial decision-making.

Purpose Digital transformation is crucial for optimizing firms' business process management (BPM), yet few studies have examined it from a digital BPM lifecycle perspective. This study investigates whether and how technological competition affects the alignment between strategic commitment and actual actions across the digital BPM lifecycle. Design/methodology/approach We construct a digital decoupling measure by capturing the gap between firms' digital commitment and actions using text analysis. We then use panel data of Chinese listed companies from 2012 to 2023 to test the proposed relationships. Findings We find that technological peer pressure positively influences firms' digital decoupling behavior, with managerial myopia and market share loss acting as mediating factors. The moderating results show that patient capital weakens the positive effect of technological peer pressure on digital decoupling. Heterogeneity analyses further indicate that this effect is more pronounced among firms with weaker BPM capability and higher business process complexity. Originality/value This study conceptualizes digital decoupling from a digital BPM lifecycle perspective. It extends research on firms' digital behavior under competitive pressure, the determinants of digital BPM capability development, and the assessment framework for digital BPM capability. The findings offer actionable guidance for firms to reduce digital decoupling and help regulators identify priorities and measures to monitor and mitigate it.

Purpose Integrating artificial intelligence (AI) technologies into knowledge management systems (KMSs) offers transformative potential for organizations by enhancing knowledge-intensive business processes. However, this integration may face barriers and challenges. This study investigates the organizational implications for effective change management and structured implementation processes required for a beneficial integration of AI into KMSs. Design/methodology/approach A quantitative research design was employed using an online survey developed for this study and completed by 378 professionals across diverse roles, organizational sizes, and sectors. The instrument assessed perceptions of four barrier categories – human, technological, financial, and ethical-regulatory – through validated multi-item scales. Statistical analyses, including repeated-measures ANOVA, MANOVA, and t-tests, were conducted to identify differences across demographic and organizational variables. Findings Technological and ethical-regulatory barriers are perceived as more significant than financial ones. Managers identified human-centered hurdles, such as resistance to change and skills gaps, as more immediate threats than financial constraints. Knowledge managers expressed significant concerns regarding technical integration with existing KMSs. Smaller organizations reported higher levels of human and technological complications compared to medium and large firms. Graduates demonstrated greater sensitivity to ethical-regulatory issues, whereas the high-tech sector perceived fewer obstacles overall. No significant differences emerged across gender, age, or seniority. Originality/value By connecting established models of technology adoption with empirical evidence from knowledge-intensive contexts, this study strengthens understanding of AI integration within KMSs as a socio-technical process shaped by organizational contingencies and governance imperatives. It contributes to the literature on business process management by framing AI integration as a process-oriented transformation rather than a purely technological upgrade.

Purpose This study aims to analyze the stressors perceived by professionals in Big Data Organizational Environments (BDOE) to identify potential situational stimuli that may trigger negative internal states impairing professional performance. Design/methodology/approach An exploratory qualitative study was conducted, drawing on elements of Grounded Theory Methodology. Based on interviews with 40 professionals in BDOEs, we examined their experiences through the lens of the Transactional Theory of Stress and Coping (TTSC). Findings The findings synthesize three primary stressor dimensions: (1) data characteristics (volume, variety, velocity, veracity); (2) work characteristics (workload, uncertainty, complexity, deadlines, job market); and (3) data literacy gaps (supervisors, colleagues, self-assessment). Notably, we analyze the critical tensions and combinatorial dynamics among these categories to develop new theoretical propositions through the lens of TTSC. Research limitations/implications This study contributes to the theory by shifting the focus from organizational challenges to individual stressors and by identifying BDOE stressors from professionals’ perspectives, beyond data stressors. Practical implications This study provides managers with insights into how stressors can be mitigated by reducing the workload, addressing unrealistic expectations, and investing in data literacy across all hierarchical levels. Social implications This paper highlights the cognitive and emotional burdens of working in data-driven environments, with implications for workforce well-being and sustainable digital transformation. Originality/value The empirical evidence clarifies how BDOE can be difficult for individuals, offering insights into stressors from the perspective of professionals who experience them. Therefore, this study allows reflection on which other circumstances, combined with data stressors, might also be perceived as stressors and negatively affect professionals’ performance, thereby shedding light on the dark side of BDOE.

Purpose Food loss, climate variability, resource constraints and growing demand are placing agri-food supply chains (AFSCs) under mounting pressure to deliver sustainable food security (SFS). Digital twin (DT) technology is a promising approach to overcoming these challenges through capabilities such as real-time monitoring, increased visibility and data-driven decision-making. Nevertheless, the implementation of DTs in AFSC is still in its early stages and faces significant challenges. Design/methodology/approach Using Resource Orchestration Theory (ROT), the paper elaborates on how the failure to structure, bundle and leverage resources limits the implementation of DT. Moreover, this paper also investigates the interactions and hierarchical links among these challenges by employing a hybrid approach that combines the Delphi method with the Interpretive Structural Model (ISM) and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology. Findings From a review of the literature and expert insights, the study identifies 13 key challenges. To effectively implement DT and address food security concerns, special attention must be paid to key structuring challenges, such as high costs and the Lack of a single digital platform and standard architecture, which become fundamental factors restricting the diffusion of DT. Research limitations/implications This research provides a critical theoretical and practical framework for policymakers, technology providers and agri-food firms to strategically orchestrate their resources, thereby overcoming adoption hurdles and harnessing DT technology to make substantive progress towards Sustainable Development Goal 2 (SDG 2), i.e. Zero hunger through SFS. Originality/value Unlike the previous studies on DT adoption in AFSCs, which mainly determine the challenges to DT adoption through descriptive or single-method approaches (e.g. Yadav and Majumdar, 2024). To the best of the authors’ knowledge, this study is the first to apply the ROT to a Delphi–ISM–MICMAC–DEMATEL approach, systematically modeling the hierarchical and causal relationships among DT adoption challenges. This provides not only a profound theoretical explanation but also decision-oriented insights for SFS.

Purpose Manufacturing firms face increasing stakeholder pressure to optimize business processes, improve waste management and enhance sustainable performance (SP). Achieving these objectives requires the strategic implementation of green initiatives, sustainable practices and digitalization. Given this, the study investigates how green entrepreneurial orientation (GEO) influences SP through the mediating role of circular economy practices (CEPs) and the moderating role of digital capability (DC). Design/methodology/approach Data were collected using a two-wave time-lagged field survey from 543 manufacturing MSMEs in Nigeria. Partial least squares structural equation modeling (PLS-SEM) was conducted using SmartPLS 4 to analyze the data. Findings The results indicate that GEO has a positive and significant effect on both CEP and SP. Furthermore, CEP partially mediates the relationship between GEO and SP, suggesting that the influence of GEO on SP also operates indirectly through CEP. In addition, the results show that DC significantly moderates the relationship between GEO and CEP, while its moderating effect on the GEO–SP relationship is not significant. Originality/value This study is among the first to empirically examine the interconnected relationships among GEO, CEP, DC and SP through the lens of dynamic capabilities theory. It also provides actionable insights for manufacturing MSMEs on formulating policies and strategies that strengthen CEP and, in turn, enhance SP.

Purpose The purpose of this study is to examine internationalisation processes among micro, small and medium enterprises involved in a leading industry and operating in emerging economies. The study uses a cross-national approach and considers the conceptual underpinnings of the dynamic capabilities approach as its conceptual background. Design/methodology/approach The perspectives of enterprise leaders operating in five coffee-producing nations were gathered through semi-structured, open-ended interviews. Findings Opportunities in internationalisation processes include the rising global demand, value-adding potential, image enhancement and self-initiated improvements in the production processes. However, participants also recognise existing inadequate business models to cope with higher quality demands or the market's competitiveness. To evolve, developing stronger adaptive processes is crucial for meeting the continuous pressures of quality standards, supply consistency and perennially unpredictable factors, including prices and the climate. Conceptually, the analysis uncovered 13 conceptual dimensions that inspired a conceptual framework, reinforcing and extending the dynamic capabilities framework. Originality/value While research on firm internationalisation processes is a mature area of inquiry, the focus on micro, small- and medium-sized firms operating in emerging economies using a cross-national approach has been more limited. This study helps narrow this gap, providing original and valuable insights into business processes concerning a global product. The study's analysis and resulting conceptual contributions underscore important implications associated with firm and industry internationalisation processes among emerging economies operating in a significant industry.

Purpose This article investigates the effect of business intelligence (BI) capacity on the adoption of circular economy (CE) practices. Drawing on the quality of decision-making as a mediator and innovation climate (IC) and continuous improvement (CI) as moderators, it takes the research on open innovation process practices further. Through the resource-based view (RBV)/dynamic capabilities (DC) view, the study explains a conditional-process model that separates the bundles of BI capabilities (sensing, transforming and driving). In this model, decision-making quality (DMQ) is the middle link. IC and CI are the outside conditions that influence the results. Design/methodology/approach The study employed a quantitative research design. The data was derived from a sample of 360 employees in governmental organizations throughout the United Arab Emirates (UAE). Structural equation modeling using partial least squares was employed for data analysis. The model examines three types of pathways: direct effects, indirect effects where BI influences CE outcomes through DMQ, and moderated effects, in which IC shapes the relationship between BI and DMQ, while CI influences the link between DMQ and CE outcomes. This analytical structure provides theory-driven evidence that extends beyond mere correlation. Findings The results reveal that those BI capabilities, particularly driving and transforming capabilities, positively influence CE implementation by enhancing DMQ. Sensing capability showed no meaningful effect. This result shows that just having good information awareness is not enough. It needs support from action-focused capabilities, like transforming and driving, to produce outcomes linked to CE. Additionally, an innovation-supportive climate strengthens the relationship between BI capabilities and DMQ, while CI practices amplify the link between DMQ and CE implementation. Taken together, the results show a pathway that moves from capability to process to outcome. They also explain where the moderators play a role: IC works at the early stage, while CI acts at the later stage, all within the UAE public sector context. Originality/value This study contributes to the literature by integrating BI capabilities, decision-making processes and organizational climate factors in the context of CE. The new value of this paper comes from three points. First, it separates BI capability bundles from the wider ideas of big data analytics. Second, it identifies DMQ as a small but key foundation that connects BI to CE results. Third, it sets IC and CI as the outside conditions that stretch RBV/DC beyond simple consolidation. All of this is shown with public-sector evidence from the UAE. It underscores the strategic value of aligning technological and cultural enablers to drive sustainable practices in public sector organizations.

Purpose Although research demonstrates that big data analytics capability (BDAC) plays a vital role in improving firm performance, the mechanisms and conditions behind this relationship remain unclear. To address this gap, this study explores the mechanism and conditions by testing the mediating role of strategic orientation ambidexterity and examining the moderating role of team heterogeneity and team reflexivity. Design/methodology/approach This study applies ambidexterity theory and upper echelons theory as the theoretical lenses and uses a structural equation modeling approach to empirically test the proposed model with the cross-sectional survey data from 350 Chinese firms. Findings Strategic orientation ambidexterity positively mediates the relationship between BDAC and firm performance. In addition, both team heterogeneity and team reflexivity not only strengthen the direct effect of BDAC on strategic orientation ambidexterity but also positively moderate the indirect effect of strategic orientation ambidexterity. Originality/value This study not only narrows the knowledge gap left by earlier work that overlooked identifying the mechanism of the relationship between BDAC and firm performance from an ambidextrous perspective but also extends the managerial literature by addressing internal conditions. It offers theoretical insights for managers to improve firm performance by aligning BDAC, multiple strategic orientations and team members’ characteristics.

Purpose This research synthesizes the existing empirical research into the role of green intellectual capital (IC) in the sustainable performance (SUSP) of organizations through meta-analysis. Specifically, it evaluates the overall and comparative effect of each green IC dimension, green human capital (HC), green structural capital (SC) and green relational capital (RC), on economic performance (ECP), social performance (SP) and environmental performance (EP). Design/methodology/approach A meta-analysis is conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework, synthesizing 77 studies (N = 23,691) from Web of Science and Scopus. Effect sizes are estimated using Fisher's r-to-z transformation and pooled random-effects models via the metafor package in R. Heterogeneity and publication bias are assessed, and subcategory analyses examine the effects of green human capital, green structural capital and green relational capital on ECP, social performance and environmental performance. Findings This meta-analysis synthesizes 77 studies examining the link between green IC dimensions and ECP, SP and EP. The findings indicate a positive significant correlation between overall green IC and SUSP. Green HC, green SC and green RC appear as the most prominent dimensions, indicating a positive, direct and significant connection with SUSP. Pooled correlations range from r = 0.3774 to 0.7319 across overall green IC and its dimensions. The I2 score values (ranging from 89.29% to 99.91%) and the Q values (ranging from 80.2274 to 1050.1002), at the 95% prediction confidence interval, show that the meta-analysis models display significant heterogeneity. A visual illustration of the outcomes in the form of a forest plot fortifies the reliability of the finding that green IC serves as a crucial driver of SUSP. These findings highlight an in-depth understanding of green IC dimensions and their association with SUSP. Originality/value This study fills gaps in the existing literature by providing a comprehensive meta-analysis focused on green IC and its dimensions along with ECP, EP and SP. The study provides nuanced insight into how green IC and its dimensions influence the three facets of SUSP.