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The purpose of this paper is to understand how reverse resource exchanges and resource dependencies are managed in the service supply chain (SSC) of returnable transport packaging (RTP).

A single case study was conducted in the context of automotive logistics focusing on the RTP SSC. Data were collected through 16 interviews, primarily with managers of a logistics service provider (LSP) and document analysis of contractual agreements with key customers of the packaging service.

Resource dependencies among actors in the SSC result from the importance of the RTP for the customer’s production processes, the competition among users for RTP and the negative implications of the temporary unavailability of RTP for customers and the LSP (in terms of service performance). Amongst other things, the LSP is dependent on its customers and third-party users (e.g. the customer’s suppliers) for the timely return of package resources. The role of inter-firm integration and collaboration, formal contracts as well as customers’ power and influence over third-party RTP users are stressed as key mechanisms for managing LSP’s resource dependencies.

A resource dependence theory (RDT) lens is used to analyse how reverse resource exchanges and associated resource dependencies in SSCs are managed, thus complementing the existing SSC literature emphasising the bi-directionality of resource flows. The study also extends the recent SSC literature stressing the role of contracting by empirically demonstrating how formal contracts can be mobilised to explicate resource dependencies and to specify, and regulate, reverse exchanges in the SSC.

The research suggests that logistics providers can effectively manage their resource dependencies and regulate reverse exchanges in the SSC by deploying contractual governance mechanisms and leveraging their customers’ influence over third-party RTP users.

The study is novel in its application of RDT, which enhances our understanding of the management of reverse exchanges and resource dependencies in SSCs.

To study how supply chain decision makers gather, process and use the available internal and external information when facing supply chain disruptions.

The paper reviews relevant supply chain literature to build an information management model for disruption management. Afterwards, three case studies in the vehicle assembly sector, namely cars, trucks and aircraft wings, bring the empirical insights to the information management model.

This research characterises the phases of disruption management and identifies the information companies use to recover from a variety of disruptive events. It presents an information management model to enhance supply chain visibility and support disruption management at the operational level. Moreover, it arrives at two design propositions to help companies in the redesign of their disruption discovery and recovery processes.

This research studies how companies manage operational disruptions. The proposed information management model allows to provide visibility to support the disruption management process. Also, based on the analysis of the disruptions occurring at the operational level we propose a conceptual model to support decision makers in the recovery from daily disruptive events.

The purpose of this paper is to investigate the implications of supply chain strategies that manufacturing companies can use to minimise or overcome natural resource scarcity, and ultimately improve resource efficiency and achieve competitive advantage. The relationship between resource efficiency and competitive advantage is also explored.

The proposed research model draws on resource dependence theory. Data were collected from 183 logistics, purchasing, sustainability and supply chain managers from various manufacturing companies and analysed by applying the partial least squares structural equation modelling technique.

The results indicate that both buffering and bridging strategies improve resource efficiency; however, only bridging strategies seem to lead to firm’s competitive advantage in terms of ownership and accessibility to resources. The relationship between resource efficiency and competitive advantage is not supported.

Future research could confirm the robustness of these findings by using a larger sample size and taking into account other supply chain members.

This research provides guidance to managers faced with the growing risk of resource scarcity to achieve a resource efficient supply chain and an advantage over competitors.

Studies have explored the appropriate strategies for minimising dependencies caused by the scarcity of natural resources in the field of supply chain management; however, there is limited empirical work on investigating the impact of these strategies on resource efficiency and competitive advantage.

The purpose of this paper is to explore the implications of natural resource scarcity (NRS) for companies’ supply chain strategies.

Drawing on the resource dependence theory (RDT), a conceptual model is developed and validated through the means of exploratory research. The empirical work includes the assessment of qualitative data collected via 22 interviews representing six large multinational companies from the manufacturing sector.

When the resources are scarce and vitally important, companies use buffering strategies. Buffering and bridging strategies are preferred when there are a few alternative suppliers for the specific resource and when there is limited access to scarce natural resources.

The research focuses on large multinational manufacturing companies so results may not be generalised to other sectors and to small- and medium-sized firms. Future research needs to examine the implications of NRS for organisational performance.

This research provides direction to manufacturing companies for adopting the best supply chain strategy to cope with NRS.

This paper adds to the body of knowledge by providing new data and empirical insights into the issue of NRS in supply chains. The RDT has not been previously employed in this context. Past studies are mainly conceptual and, thus, the value of this paper comes from using a qualitative approach on gaining in-depth insights into supply chain-related NRS strategies and its antecedents.

The purpose of this paper is to investigate dependencies that arise between companies during the ramp-up of production volume in the electric vehicle (EV) supply chain.

An inter-company case study method has been used. Data were collected via tours of manufacturing plants, workshops and interviews from multiple tiers in a supply chain, namely, a niche EV manufacturer, as well as two of its tier-one suppliers and five of its tier-two suppliers.

As production volumes increased, a more relational approach was found to be necessary in inter-company relationships. The authors’ research showed that key suppliers, in addition to providing the parts, pursued a supply chain orchestrator’s role by offering direct support and guidance to the niche EV manufacturer in designing and executing its development plans.

The resource dependence theory (RDT) is used to analyse and explain the changing dependencies throughout the planning and execution of production ramp-up.

This study will help supply chain managers to better manage resource dependencies during production ramp-up.

This study explores dependencies during the early stages of the production ramp-up process in the EV sector, which is in itself in the early stages of evolution. RDT is used for the first time in this context. This study has moved beyond a simple dyadic context, by providing empirical insights into the actions taken by an EV manufacturer and its suppliers, towards a multi-tier supply chain context, to better manage resource dependencies.

The study aims to define a research agenda for creating resource-efficient supply chains (RESCs) by identifying and analysing their key characteristics as well as future research opportunities.

We follow a systematic review method to analyse the literature and to understand RESC, taking a substantive theory approach. Our approach is grounded in a specific domain, the agri-food sector, because it is an intensive user of an extensive range of resources.

The review shows that works of literature has looked at the use of resources primarily from the environmental impact perspective. There is a need to explore whether or not and how logistics/supply chain decisions will affect the overall configuration of future food supply chains in an era of resource scarcity and depletion and what the trade-offs will be.

The paper proposes an agenda for future research in the area of RESC. The framework proposed along with the key characteristics identified for RESC can be applied to other sectors.

Our research should facilitate further understanding of the implications and trade-offs of supply chain decisions taken on the use of resources by supply chain managers.

The paper explores the interaction between supply chains and natural resources and defines the key characteristics of RESC.

The purpose of this paper is to conceptualize e‐business adoption and to generate understanding of the range of factors affecting the adoption process. The paper also aims at exploring the perceived impact of e‐business adoption on logistics‐related processes.

Case study research, by conducting in‐depth interviews in eight companies.

E‐business adoption is not exclusively a matter of resources. Increased e‐business adoption and impact are caused by increased operational compatibility, as well as increased levels of collaboration. In terms of e‐business impact this mainly refers to cycle time reductions and quality improvements, rather than direct cost reductions as reported by other authors.

The intrinsic weakness of the research method and the way concepts are operationalized limits the ability to generalize findings.

Managers should emphasize developing their relationships with their suppliers/customers, in an effort to do common e‐business investments, and should aim to increase their partners' commitment to the use of these applications.

This paper provides empirical evidence from a sector where limited research efforts have taken place. Explanations can be helpful to other researchers involved in the understanding of the adoption of e‐business and its impact.

The purpose of this paper is to develop an innovative information hiding algorithm.

The proposed algorithm is based on image histogram statistics. Cumulative‐peak histogram regions are utilized to hide multiple bits of the secret message by performing histogram bin substitution. The embedding capacity, otherwise known as payload, and peak signal to noise ratio (PSNR), as well as security, are the main metrics used to evaluate the performance of the proposed algorithm.

According to the obtained results, the proposed algorithm shows high embedding capacity and security at comparable PSNR compared with existing hiding information techniques.

The simplicity, security, random distribution of embedding pixels, and on‐demand high capacity are the key advantages of the proposed approach.

A huge amount of data are produced in the agriculture sector. Due to the huge number of these datasets it is necessary to use data analysis techniques in order to comprehend the data and extract useful information. The purpose of this paper is to measure, archetype and mine olea europaea production data.

This work applies three different data mining techniques to data about Olea europaea var. media oblonga from the island of Thassos, at the northern part of Greece. The data were from 1,063 farmers from three different municipalities of Thassos, namely Kallirachi, Limenaria and Prinos and concerned the year 2010. They were analysed using the classification algorithm OneR, the clustering algorithm k‐means and the association rule mining algorithm, Apriori from the WEKA data mining package. Also, new measures which quantify the performance of the productions of olives and oil are applied. Finally, archetypal analysis is applied in order to distinguish the most typical/stereotype farms for each region and describe their specific characteristics.

The results indicate that organic cultivation could improve the production of olives and olive oil. Furthermore, the climate differences among the three municipalities seems to be a factor involved in production efficacy.

It is the first time that data from the island of Thassos have been analysed systematically using a variety of data mining methods. Also, the measures proposed in the paper in order to analyse the data are new. Furthermore, archetypal analysis is proposed as a method to extract sterotypes/representative farms from the dataset.