Conference Agenda

Exporters can access foreign markets through various channel arrangements, including direct exporting, Export Management Companies (EMCs), Export Trading Companies (ETCs), piggybacking arrangements, and foreign distributors. While existing research has largely focused on control, resource commitment, and market uncertainty as determinants of export channel choice, the role of logistics conditions remains underexplored. This study examines how logistics performance influences the suitability of alternative export intermediaries across different international market environments.
A multi-criteria decision-making framework is developed to evaluate five export channel alternatives using nine criteria: market access capability, local market intelligence, degree of control, resource commitment, risk exposure, logistics coordination capability, customs and regulatory support, adaptability to low-performance logistics environments, and supply chain resilience. The World Bank Logistics Performance Index (LPI) is used to classify target markets into high-, medium-, and low-performance logistics environments. Expert judgments are collected to assess the relative importance of the evaluation criteria and the suitability of export channel alternatives under each scenario. The CRITIC-BWM method is employed to determine criterion weights and rank the alternatives.
The study contributes by introducing logistics performance as a determinant of export intermediary selection and by integrating export channel and logistics management perspectives. The findings provide a decision framework that helps exporters align intermediary choices with the logistics realities of target markets. Furthermore, the study offers insights into how changing logistics environments influence the effectiveness of alternative export channels and supports more resilient international market entry strategies.

Purpose - When employees give robots or AI agents names, talk to them, or feel anxious when they malfunction, they are revealing a fundamental human response to technology. As autonomous systems become increasingly integrated into retail logistics, an important question arises: How does working with robots and AI affect the people who interact with them? This article examines psychological and physiological reactions to human-technology collaboration (HTC), ranging from anthropomorphism and emotional attachment to technostress, social isolation, and feelings of surveillance or displacement (Cadario et al., 2021; Schlund & Zitek, 2024; Sapkota et al., 2025; Kayas et al., 2025). Although cobots and AI agents differ technologically, both can reduce perceived autonomy, blur the boundaries of agency, and trigger similar affective reactions. We therefore advocate for an integrated, human-centric perspective on technology acceptance and hybrid work systems in future retail logistics.

Approach - This paper proposes a two-pronged framework for action. Employees can form parasocial relationships with robots by attributing social characteristics to the machines and even giving them names (Schömbs et al., 2023; Leichtmann et al., 2025; Berretta et al., 2023). Conversely, collaboration between humans and technology can undermine autonomy, social connectedness, and professional identity. AI-supported systems can further exacerbate these effects through novel stressors - such as unpredictability, social erosion, and job insecurity - thereby creating new occupational health risks in retail logistics (Sapkota et al., 2025).

Design/methodology - Building on previous research on psychophysiological stress in logistics work (Hagemann et al., 2021; Keil et al., 2025; Keil & Klumpp, 2025), this paper develops a conceptual model of human reactions to robots and AI systems, ranging from attachment and trust to alienation and stress. By integrating findings from the fields of anthropomorphism (Schömbs et al., 2023; Tang et al., 2023; Glikson & Woolley, 2020), parasocial relationships (Gambino et al., 2020), and psychophysiological stress research (Orlando et al., 2025; Pereira et al., 2025), the model establishes a human-centric perspective on hybrid work systems in retail logistics. Picking in the warehouse serves as an illustrative context for human-technology collaboration, due to the close interaction between employees and autonomous systems (Klumpp et al., 2022; Tudisco et al., 2026).

Practical implications - What happens when employees form an emotional attachment to technologies that are later replaced, or when they feel increasingly monitored by AI? Research links AI-supported work, job insecurity caused by automation, and digital surveillance to emotional exhaustion and depressive symptoms. Since cobots and AI are viewed as technologies that reshape both work processes and employee experiences, this article advocates for a human-centric research agenda. This agenda places employee well-being - on an equal footing with operational efficiency - at the center as a key design goal for Industry 5.0 and Warehousing 5.0 (Rieth et al., 2024; Hagemann et al., 2026).

Third-party conformity assessment under ISO/IEC 17065 represents a pivotal governance mechanism for railway safety assurance. While non-accredited assessments may overlook critical system hazards leading to catastrophic failures and losses, mandating rigorous ISO-compliant processes demands additional financial overhead and procedural burdens. Thus, evidence guiding these accreditation mandates remains scarce, particularly in emerging railway markets. To address this gap, this study proposes a comprehensive probabilistic framework that quantitatively evaluates the systemic and economic impacts of accreditation rigour conditioned by institutional enforcement quality across four Safety Integrity Levels (SILs) and a Basic Integrity baseline.

Employing a quantitative risk evaluation methodology with stochastic parameter ranges, the framework can determine residual hazard rates as a function of SIL-specific baselines, an Intrinsic Rigour Score (K₀), the instructional effectiveness of the railway authority (β) and enforcement-conditioned certification effectiveness. , extracted from ISO/IEC 17065, critically imposes verifiable requirements for technical competence, impartiality and procedural rigour on certification bodies. serves as a weight-sum representation of the railway regulatory maturity index, government effectiveness and control of corruption. Finally, to translate technical safety outcomes into an economic justification metric, the derived residual hazard rates are converted into lifecycle expected losses by factoring in total operational hours and heavy-tailed consequence costs per event.

A 2 × 2 × 5 factorial design (accreditation status, enforcement profile, and SILs) was evaluated through extensive computational simulations. The proposed framework establishes a quantitative link between institutional regulatory inputs and high-consequence safety outcomes. The model is formulated, demonstrating how variations in safety integrity requirements alter the financial breakeven financial thresholds for mandatory accreditation and technical competence for certification bodies. By capturing the divergence between expected-value economic metrics and heavy-tailed risk distributions, the model directly supports the ALARP principle and precautionary regulatory decision-making. Ultimately, this research delivers a replicable, multi-tiered evaluation methodology. It provides policy-makers and railway authorities with a robust, evidence-based structural tool to confidently justify and integrate mandatory ISO/IEC 17065 technical qualification directly into infrastructure procurement specifications.