Relational asymmetry, trust, and innovation in supply chain management: a non-linear approach

A Systematic Literature Review of the IT-Based Supply Chain Management System: Towards a Sustainable Supply Chain Management Model

The concept of sustainability has been highly valued by all aspects of life, while the supply chain plays a critical role in production and logistics. Supply chain management (SCM) is continuously transformed by information technology (IT). The purpose of this study is to review and discuss the effect of information technology-based SCM on sustainability. This paper conducted a systematic literature review by collecting author-anchored keywords from peer-reviewed articles on IT-based supply chain management. A total of 1264 articles and 2575 keywords from eleven supply chain-related journals were analysed with social network analysis. A knowledge map with ten research hot topics was identified. Additionally, a sustainable supply chain management (SSCM) model is developed not only to guide researchers to further understand IT-based SCM topical and structural meanings but also to contribute to enlightening a coherent and rigorous body of theories relevant to academics and supply chain and logistics managers interested in SSCM.

A systematic review of responsiveness to develop future research agenda: a TCCM and bibliometric analysis

Purpose

This paper aims to epistemologically extend and explore the present theories from prior research conducted in the area of responsiveness. Furthermore, it determines to benchmark the prominent theories, characteristics, context and methodologies (TCCM) used in the domain since its inception to advance the science and practice of marketing and logistics discipline.

Design/methodology/approach

A seven-step methodology (SSM) has been introduced to create a comprehensive dataset. Based upon the selection criteria of high-ranked journals and language, the research studies have been retrieved from Scopus, Web of Science, Business Source Complete and journal homepage to avoid the error of exclusion. Moreover, the dataset has been compiled using manual and electronic searches without any limitation of time.

Findings

The search for a suitable dataset retrieved 642 documents by identifying “1969” as the beginning year of research in the subject domain. The analysis found that responsiveness has been prominently studied in the manufacturing industry. The results also advocate responsiveness as the vital antecedent to performance and satisfaction. Frameworks have been proposed with significant propositions for future empirical testing and theory inventiveness by researchers.

Originality/value

The study pioneers its utility for retailers to recognize the firms' inherent abilities and strengths, which can be promoted to create responsiveness more than ever. The analysis results can act as the compelling force to understand the driving power of various factors influencing responsiveness.

Investigating the role of demand planning as a higher-order construct in mitigating disruptions in the European supply chains

Purpose

The goal of the paper is twofold. First, it aims to empirically conceptualize whether a wide array of fragmented demand planning activities, performed in supply chains, can be logically categorized into actionable sets of practices, which then form a broader conceptualization of the demand planning process. Second, regarding certain contextual factors, our research seeks to investigate the contribution of demand planning, as a higher-order construct, to mitigating disruptions induced by operational risks in supply chains.

Design/methodology/approach

In this study, PLS-SEM was used to estimate the reflective-formative nature of the model. The results of PLS-SEM were additionally complemented by the assessment of the predictive power of our model. Finally, to reveal possible contingency effects, the multigroup analysis (MGA) was conducted.

Findings

The study suggests that demand planning process (DPP) is a second-order construct that is composed of four sets of practices, including goal setting, data gathering, demand forecasting, communicating the demand predictions and synchronizing supply with demand. The study also reveals that the demand planning practices, only when considered together, as a higher-order factor, significantly contribute to mitigating disruptions driven by operational risks. Finally, the research shows that the strength of the impact of demand planning on disruptions is contextually dependent.

Research limitations/implications

While the study makes some important contributions, the obtained findings ought to be considered within the context of limitations. First, the study only investigates disruptions driven by operational risks, ignoring the negative consequences of environmental risks (terrorist attacks, natural disasters, etc.), which may have a far more negative impact on supply chains. Second, the sample is mostly composed of medium and large companies, not necessarily representative of demand planning performed by the entire spectrum of companies operating in the market.

Practical implications

The study shows that to effectively mitigate disruptions induced by operational risks, the demand planning practices should be integrated into a higher-order construct. Likewise, our research demonstrates that the intensity of demand planning process is contingent upon a number of contextual factors, including firm size, demand variability and demand volume.

Social implications

The study indicates that to mitigate disruptions of operational risk, demand planning as a higher-order dynamic capability can be referred to the concept of organizational learning, which contributes to forming a critical common ground, ensuring the balance between formal and informal dynamic routines.

Originality/value

The paper depicts that to fully deal with disruptions, the demand planning practices need to be integrated and categorized into the dedicated higher-order. This may lead to forming demand planning as a higher-order dynamic capability that provides a more rapid and efficient rebuttal to any disruptions triggered by operational risks.

An Event-Based Supply Chain Partnership Integration Using a Hybrid Particle Swarm Optimization and Ant Colony Optimization Approach

Integrating a partnership with potentially stronger suppliers is widely acknowledged as a contributor to the organizational competitiveness of a supply chain. This paper proposes an event-based model which lists the events related with all phases of cooperation with partners and puts events into a dynamic supply chain network in order to understand factors that affect supply chain partnership integration. We develop a multi-objective supply chain partnership integration problem by maximizing trustworthiness, supplier service, qualified products rate and minimizing cost, and then, apply a hybrid algorithm (PSACO) with particle swarm optimization (PSO) and ant colony optimization (ACO) that aims to efficiently solve the problem. It combines the advantages of PSO with reliable global searching capability and ACO with great evolutionary ability and positive feedback. By using the actual data from 1688.com, experimental studies are carried out. The parameter optimizing of the hybrid algorithm is firstly deployed and then we compare the problem solution results of PSACO with the original PSO, ACO. By studying the partnership integration results and implementing analysis of variance (ANOVA) analysis, it shows that the event based model with PSACO approach has validity and superiority over PSO and ACO, and can be served as a tool of decision making for supply chain coordination management in business.