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The purpose of this paper is to explore the effect of inventory record inaccuracy due to behavioral aspects of workers on the order and inventory variance amplification.

The authors adopt a continuous-time analytical approach to describe the effect of inbound throughput on the inventory and order variance amplification due to the workload pressure and arousal of workers. The model is numerically solved through simulation and results are analyzed with statistical general linear model.

Inventory management policies that usually dampen variance amplification are not effective when inaccuracy is generated due to workers’ behavioral aspects. Specifically, the psychological sensitivity and stability of workers to deal with a given range of operational conditions have a combined and multiplying effect over the amplification of order and inventory variance generated by her/his errors.

The main limitation of the research is that the authors model workers’ behavior by inheriting a well-known theory from psychology that assumes a U-shaped relationship between stress and errors. The authors do not validate this relationship in the specific context of inventory operations.

The paper gives suggestions for managers who are responsible for designing order and inventory policies on how to take into account workers’ behavioral reaction to work pressure.

The logistics management literature does not lack of research works on behavioral decision-making causes of order and inventory variance amplification. Contrarily, this paper investigates a new kind of behavioral issue, namely, the impact of psycho-behavioral aspects of workers on variance amplification.

This paper aims to advocate and facilitate undertaking research focused on the effects of human behaviour, judgment and decision making in logistics and supply chain management (SCM).

In addition to providing an overview of the potential benefits of behavioural research, this paper presents two modified frameworks for identifying and addressing behavioural issues in logistics and SCM.

Behavioural research can significantly advance both theory and practice in logistics and SCM. Little behavioural research appears in top logistics journals. As researchers begin to conduct more such projects, knowledge pertaining to issues of importance to logistics and SCM will be created.

This paper highlights an important research area and a methodology, (controlled behavioural experiments), that are currently underutilized in logistics and SCM. It further presents potential research questions and suggestions for ways in which interested researchers could begin to address such issues.

While the physical paths that goods traverse are being simplified, the capture, storage, processing and dissemination of information associated with logistics has become considerably more complex. Logistics researchers need to better understand the behavioral and managerial issues created by information technology implementation. The paper suggests that structuration theory, a research approach derived from sociology that has become well established in the study of information systems, can contribute to that understanding. This paper introduces logistics researchers to structuration theory as a useful theoretical framework that can help understand the relationship between technologies, the people who interpret them, and the patterns of use that stem from that interpretation.

The purpose of this paper is to advance supply chain management by describing the current state of behavioral supply chain management (BSCM) research and paving the way for future contributions by developing a meta-theory for this important field.

The results are generated by applying the systematic literature review methodology and an iterative theory-building approach involving a panel of academics.

This review provides a comprehensive overview of the BSCM research landscape. Additionally, a meta-theory of BSCM is presented that encompasses all central elements of the research field and introduces the concept of emergence to the field of BSCM. Furthermore, five promising future research opportunities are formulated.

The critical discussions and the formulated research opportunities will help scholars in positioning their research to enhance its contribution.

Results from this research indicate that supply chain decisions benefit from explicit consideration for cognitive and social phenomena.

This review is the first to provide a comprehensive overview of the field of BSCM research and facilitates BSCM in advancing further.

Because of the major contribution of logistics to the greenhouse gas effect, logistics research has begun to address the topic of energy, but it has not yet targeted the role of energy within logistical decision-making processes. To facilitate such endeavors, the purpose of this paper is to explore the perceptions of energy which managers in logistics organizations portray.

This investigation is based on interviews with 17 managers. The findings are embedded in the theory of planned behavior (TPB) and stakeholder theory (SHT).

The study depicts initial insights on which energy-related perceptions exist, how they can be categorized into attitudes, subjective norms, and perceived behavioral controls (PBCs), and how different stakeholders seem to affect them.

This research suggests a tentative comprehensive conceptual framework that describes the role of energy in logistical decision-making processes. The findings on attitudes and subjective norms appear to be unspecific to the logistics domain, whereas some of the PBCs are presumably unique to the logistics context. Future logistics research should hence focus its efforts on the PBCs. Generalizability and completeness of the managerial perceptions must be validated by future research.

The findings help logistics organizations in scrutinizing managerial perspectives on energy and in developing awareness-raising measures.

The behavioral perspective applied in this study can complement extant, more technically oriented views. The conceptual framework that integrates the TPB and SHT may also be useful for organizational research beyond the logistics domain.

In the current dynamic business environment, Internet of Things (IoT) is employed by a number of companies in the logistics industry to achieve intelligent sorting, network optimization, real-time tracking and simplifying last-mile service. Although logistics entities are trying to introduce IoT into their business areas, users' perception of this new technology is still limited. This paper aims to develop a research model for the factors influencing the user adoption of IoT technology in the logistics industry.

In this study, based on the major theories on the application of new technologies such as technology acceptance model (TAM), technology–organization–environment (TOE) and innovation diffusion theory (IDT), a new research model was established to identify factors affecting customers' behavioral intention (BI) to adopt IoT technology provided by logistics companies. In addition, the authors surveyed unspecified customers of Cainiao Logistics Network, which is in charge of the logistics operation of Alibaba Group, China's largest e-commerce company, and tested the causality between the latent variables presented in the model using the structural equation model (SEM).

This empirical study shows that the support system of a logistics company and users' innovative propensity significantly affect perceived ease of use (PEOU) and BI for logistics services to which IoT technology is applied. It also presents that users' perceived security and enjoyment significantly affect perceived usefulness (PU) and BI. In addition, it was possible to confirm that the causal structure between variables suggested by TAM that PEOU has a significant effect on PU and BI, and PU has a substantial effect on BI.

Logistics companies should expand and upgrade technical support systems so that customers can flexibly accept logistics services with IoT technology and make efforts to alleviate customers' concerns about personal information leakage. In addition, it is necessary to find customers with an inclusive attitude toward using new technologies, to induce them to become leading users of logistics devices with IoT technology and to find various ways to amplify their enjoyment. Through a strategic approach to these technical and individual factors, it will be possible to boost customers' intention to use IoT logistics services.

As far as the authors know, this paper is the first study to set significant factors that affect users' BI to use IoT technology-applied logistics services provided by logistics companies and empirically analyze the causal relationships between proposed latent variables.

The purpose of this paper is to illustrate how a systematic application of middle-range theorizing, which pays particular attention to contexts and mechanisms, can be used to extend current knowledge on logistics customer service (LCS) in a number of critical areas.

The paper applies Stank et al.’s (2017) framework for middle-ranging theorizing in logistics to develop a research framework and agenda that can guide future LCS research. Results are generated through a review of the LCS literature and an application of the main concepts of middle-range theorizing.

The paper outlines opportunities for middle-range research that would extend LCS knowledge in the areas of human and behavioral factors, time-based competition, supply chain complexity, and digitization and technological innovation.

Describing the main characteristics of middle-range theorizing and how middle-range theorizing can be fruitfully applied to LCS research should help to stimulate new knowledge creation in this important area of supply chain logistics management.

By focusing on why and when questions, middle-range theorizing engages with the practical realities of LCS that interest managers and students. Middle-range theorizing moves researchers toward developing a detailed understanding of what actually has to change in order for desired LCS-related outcomes to occur and the contextual factors likely impacting the change process. The paper should, therefore, allow managers to better translate LCS theory into action.

Middle-range theorizing remains new to the supply chain logistics field. The application of middle-range theorizing to LCS research, and logistics research more generally, demands new perspectives on established relationships with the potential to drive original research in areas most relevant to managers.

This study aims to examine the effects of behavioural antecedents of collaboration in supply chain relationships on supply chain integration and performance by developing and empirically validating a model linking these constructs.

A conceptual model was developed based on the relational exchange theory, social exchange theory and resource-based view. An international survey with supply chain/logistics managers from manufacturing focal firms based in Europe, USA and Asia was conducted; they provided input on upstream and downstream relationships based on their actual interaction and experience with supply chain partners. The collected data, which reflect supply chain managers’ perceptions on the above described phenomena, were analysed using the partial least squares method.

Mutuality, reciprocity, trust and commitment are instrumental for the formation of supply chain relationships characterised by higher information integration. In turn, information integration has much stronger impact on the coordination of operational decisions related to production and demand planning than on decisions related to actual production processes, but, interestingly, the latter affects supply chain performance much more than the former.

The research could benefit from a longitudinal rather than a cross-sectional approach, incorporating multiple respondents such as representatives of supply chain partners and senior management of the focal firm, to capture potentially varying opinions on the supply chain phenomena under examination.

The results can assist supply chain decision-makers in understanding the importance of behavioural closeness between supply chain partners for the development of collaborative supply chain relationships that lead to higher integration and superior performance. Insight is provided on linkages between examined dimensions of supply chain integration. A process view of intermediate steps needed to translate collaborative relationships into higher supply chain integration and performance across the supply chain is offered.

The development and testing of an integrated model examining linkages between supply chain relationship antecedents, integration and performance is an original contribution. By proposing and confirming a sequential order of the influence of behavioural antecedents, integration dimensions and their impact on supply chain performance, the paper sets foundations of a roadmap for achieving higher supply chain performance from collaborative supply chain relationships. Finally, the paper contributes to the limited theoretical justification on the development of knowledge for assisting decision-making in SCM/logistics and its integration into models, processes and tasks.

The purpose of this paper is threefold: first, review the literature on the topic of behavioural antecedents of collaboration and their impact on supply chain integration and performance; second, lay the theoretical foundations and develop a conceptual model linking behavioural antecedents of collaboration, information integration, coordination of operational decisions and supply chain performance; and third, set out operationalisation considerations.

A conceptual model with theoretical basis on Relational Exchange Theory (RET) and extant supply chain theory is developed as a causal model that can be operationalised using structural equations modelling (partial least squares) and a “single key informant” approach.

Positive relationships between behavioural antecedents of collaboration (trust, commitment, mutuality/reciprocity), information integration, coordination of operational decisions and supply chain performance (efficiency, effectiveness) are hypothesised. RET provides adequate theoretical background that leads to the theoretical establishment of hypotheses between behavioural antecedents, supply chain integration and performance, which are worth testing empirically.

The ideas presented in this paper enrich the study of behavioural factors in supply chain management and their impact on supply chain performance, and may benefit researchers in the field. The paper also sets the scene (experimental design, measurement items) for the upcoming field research. The empirical part of the work will provide the necessary evidence for the validation of the established hypotheses.

The proposed linkages may stimulate the interest of supply chain strategists towards more collaborative relationship management and affect their decisions on the behavioural antecedents of relationship formation and management. Moreover, the proposed model may help clarify how the integration of critical operational contingencies – information, operational decisions – can help achieve superior supply chain performance.

The paper establishes a causal relationship between constructs which have not been researched (mutuality/reciprocity, coordination of operational decisions) or have been researched individually or in combination (impact of integration on performance, impact of collaboration on performance) but not in the proposed integrated way. It also addresses the challenge of lack of theoretical justification on the development of knowledge that will assist decision making in SCM/logistics and its integration into models, processes and tasks. Finally, by using RET in selecting of behavioural factors and establishing hypotheses, it adds to the body of knowledge concerning the use of interorganisational theories in supply chain relationships.

The purpose of the research is to conduct an exploratory investigation of the material handling activities of an Italian logistics hub. Wearable sensors and other smart tools were used for collecting human and environmental features during working activities. These factors were correlated with workers' performance and well-being.

Human and environmental factors play an important role in operations management activities since they significantly influence employees' performance, well-being and safety. Surprisingly, empirical studies about the impact of such aspects on logistics operations are still very limited. Trying to fill this gap, the research empirically explores human and environmental factors affecting the performance of logistics workers exploiting smart tools.

Results suggest that human attitudes, interactions, emotions and environmental conditions remarkably influence workers' performance and well-being, however, showing different relationships depending on individual characteristics of each worker.

The authors' research opens up new avenues for profiling employees and adopting an individualized human resource management, providing managers with an operational system capable to potentially check and improve workers' well-being and performance.

The originality of the study comes from the in-depth exploration of human and environmental factors using body-worn sensors during work activities, by recording individual, collaborative and environmental data in real-time. To the best of the authors' knowledge, the current paper is the first time that such a detailed analysis has been carried out in real-world logistics operations.