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The transition to a circular economy (CE) is a known concern in the context of the textile industry, in which business actors attempt to facilitate circular activities such as textile recycling. However, a lack of established business relationships and networks creates uncertainty for textile circulation. In such business environments, managerial decisions regarding CE may depend not only on normative behaviour but also on heuristics that guide their choices. Since business relationships for textile circularity require interactions between business actors, this study explores how managerial heuristics are shaped in the CE transition within the textile industry and their impact on actors’ interactions within business relationships and networks.

Empirically, this qualitative study is based on interviews with managers representing companies and organisations engaged in business relationships and networks aimed at a CE transition in the textile industry, as well as on publicly available secondary data.

The findings indicate that managerial decisions promoting circularity can be influenced by, besides normative information assessment, factors predominant in (1) the business and regulatory environment, (2) managers’ experience and knowledge obtained during interactions within business networks and (3) the internal strategic approaches of business organisations. This study identifies adaptation, experience, interaction and strategy heuristics that may be utilised by managers in making decisions in the context of uncertainty, such as the industrial transition to a CE.

This study expands the knowledge of heuristics applied to managerial decision making in interacting business firms and institutional organisations aiming to facilitate textile recycling and proposes a heuristics toolbox. The study provides an insight into business actors’ interactions, as well as various factors inside and outside the organisations shaping the managerial decisions. By doing this, the study adds to the literature, highlighting the importance of contextualisation and the interrelation between the individual and business environment levels in business-to-business management.

The purpose of this paper is to develop a typology of heuristics in business relationships. We distinguish between four categories: (1) general heuristics used in the context of a business relationship but that may also (and are often) used in other contexts; (2) relational context heuristics that are typically used in a relational context; (3) relational information heuristics that rely on relational information and (4) genuine relational heuristics that use relational information and are applied in relational contexts.

We draw on existing literature on heuristics and business relationships to inform our conceptual paper.

We apply this typology and discuss specific heuristics that fall under the different categories of our typology. These include word-of-mouth, tit-for-tat, imitation, friendliness, recognition and trust.

We contribute to the heuristics literature by providing a novel typology of heuristics in business relationships. Emphasizing the interdependence between heuristics and business relationships, we identify genuine relational heuristics that capture the bidirectional relationships between business relationships and heuristics. Second, we contribute to the business relationships literature by providing a conceptual framework for understanding the types of heuristics managers use in business relationships and by discussing examples of specific heuristics and how they are applied in relational contexts.

We contribute to practice by providing a simple framework for making sense out of the “universe” of heuristics for business relationships.

Our paper provides a novel typology for understanding heuristics in business relationships.

Drawing on resource orchestration theory, this paper aims to empirically investigate the relationships between digital transformation (DT), triple-A supply chain capabilities (i.e. agility, adaptability and alignment) and sustainable performance. The research focuses on the pharmaceutical industry, which best represents a business environment characterized by volatility, uncertainty, complexity and ambiguity.

Data were collected at different echelons of a globally oriented pharmaceutical supply chain, with the focal company located in the Netherlands. Empirical data were analyzed with partial least squares – structural equation modelling.

The findings reveal that DT enhances the triple-A supply chain capabilities. Nevertheless, not all three capabilities are necessary to improve overall sustainable performance. The results highlight that, among the three, only supply chain agility and adaptability significantly mediate the relationship between DT and sustainable performance.

This research supports the literature affirming that not all the triple-A supply chain capabilities equally affect sustainable performance. Moreover, it deepens the understanding of how orchestrating the triple-A capabilities at a firm level fosters overall sustainable performance, facing resource scarcity and investments in DT.

The paper aims to develop a useful tool that can reliably and accurately find the critical paths of high-rise buildings and provide optimal solutions considering the uncertainty based on Monte Carlo simulation (MCS) to enhance project implementation performance by assisting site workers and project managers in high-rise building engineering.

This research proposes an approach integrating the improved nondominated sorting genetic algorithm II (NSGA-II) considering uncertainty and delay scenarios simulated by MCS with the technique for order preference by similarity to an ideal solution.

The results demonstrate that the proposed approach is capable of generating optimal solutions, which can improve the construction performance of high-rise buildings and guide the implementation management for shortening building engineering project schedule and cost under the delay conditions.

In this study, only the construction data of the two floors was focused due to the project at the construction stage, and future work can analyze the whole construction stage of the high-rise building to examine the performance of the approach, and the multi-objective optimization (MOO) only considered two factors as objectives, where more objectives, such as schedule, cost and quality, can be expanded in future.

The approach proposed in this research can be successfully applied to the construction process of high-rise buildings, which can be a guidance basis for optimizing the performance of high-rise building construction.

The innovations and advantages derived from the proposed approach underline its capability to handle project construction scheduling optimization (CSO) problems with different performance objectives under uncertainty and delay conditions.