Search results

Grounded in contingency theory and strategic fit theory, the goal for this research was to determine if managers differentiate in terms of the degree of partnership when allocating resources for planning, joint operating controls, communication and other management components to relationships and if this differentiation is based on the Partnership Model (Lambert et al., 1996).

In total, 381 managers representing 31 relationships participated in one-and-a-half-day partnership meetings, and the authors analyzed how the management components were implemented in each relationship compared to the recommendations in the Partnership Model.

Managers did not differentiate types of partnerships which led to over-resourcing relationships with low potential and under-resourcing those with the highest potential for creating value. The principles of contingency theory and strategic fit were not used for managing relationships.

Contingency theory combined with the relationship view suggests that management components should not be implemented at the same level for all relationships, but in the 31 relationships studied different partnership types were not managed based on their potential.

The research reinforces the need for a formal structure like the Partnership Model to establish joint goals for a relationship and guide management in implementation.

Effective supply chain management depends on the ability of managers to differentiate among partnership types and fit relational mechanisms that are appropriate. However, researchers tend to generalize their findings to all partnerships regardless of potential. The authors found support for the Partnership Model published in IJLM in 1996 as a method to resource different types of partnerships following the contingency perspective and strategic fit theory.

With production systems become more digitized, data-driven maintenance decisions can improve the performance of production systems. While manufacturers are introducing predictive maintenance and maintenance reporting to increase maintenance operation efficiency, operational data may also be used to improve maintenance management. Research on the value of data-driven decision support to foster increased internal integration of maintenance with related functions is less explored. This paper explores the potential for further development of solutions for cross-functional responsibilities that maintenance shares with production and logistics through data-driven approaches.

Fifteen maintenance experts were interviewed in semi-structured interviews. The interview questions were derived based on topics identified through a structured literature analysis of 126 papers.

The main findings show that data-driven decision-making can support maintenance, asset, production and material planning to coordinate and collaborate on cross-functional responsibilities. While solutions for maintenance planning and scheduling have been explored for various operational conditions, collaborative solutions for maintenance, production and logistics offer the potential for further development. Enablers for data-driven collaboration are the internal synchronization and central definition of goals, harmonization of information systems and information visualization for decision-making.

This paper outlines future research directions for data-driven decision-making in maintenance management as well as the practical requirements for implementation.

This study aims to compare the expectations of non-collaborating professionals and the actual opinions of collaborating professionals regarding success factors of horizontal logistics collaboration (HLC) and investigates the reasons behind the observed differences.

This study employs a mixed-method approach. First, a survey is conducted to collect data from two samples representing collaborating and non-collaborating industry professionals. Second, confirmatory factor analysis (CFA) is used to compare the measurement models from the two samples and identify their similarities and differences. Third, a Delphi study is conducted to identify factors limiting collaborative behavior.

The results show that collaborating professionals exhibit lower levels of joint relationship efforts and trust than expected. This is primarily due to inadequate information sharing, poor collaboration formalization and the absence of a clear costs and benefits allocation mechanism.

The findings indicate that, in HLC, managers should give high importance to facilitating timely and complete information exchange, putting in place an acceptable costs/benefits allocation mechanism, formalizing the collaboration and prioritizing integrity over competency when selecting partners.

To the best of the authors’ knowledge, this is the first study that shows the existence of differences between industry professionals' pre-collaboration expectations and the actual experiences in HLC. This is also the first study that points to the exact HLC enablers that fail in practice and the barriers responsible for it.

As part of a national plan to govern professional and organizational development in Norwegian specialist healthcare, the country’s hospital clinics are tasked with constructing development plans. Using the development plan as a case, the paper analyzes how managers navigate and legitimize the planning process among central actors and deals with the contingency of decisions in such strategy work.

This study applies a qualitative research design using a case study method. The material consists of public documents, observations and single interviews, covering the process of constructing a development plan at the clinical level.

The findings suggest that the development plan was shaped through a multilevel translation process consisting of different contending rationalities. At the clinical level, the management had difficulties in legitimizing the process. The underlying tension between top-down and bottom-up steering challenged involvement and made it difficult to manage the contingency of decisions.

The findings are relevant to public sector managers working on strategy documents and policymakers identifying challenges that might hinder the fulfillment of political intentions.

This paper draws on a case from Norway; however, the findings are of general interest. The study contributes to the academic discussion on how to consider both the health authorities’ perspective and the organizational perspective to understand the manager’s role in handling the contingency of decisions and managing paradoxes in the decision-making process.

Transaction cost economics sees a broad spectrum of governance structures spanned by two types of economic adaptation: autonomous and cooperative. Stakeholder theorists have drawn much inspiration from transaction cost economics but have not paid explicit attention to the centrality of the idea of adaptation in this literature. This study aims to address this gap.

The authors develop a novel conceptual framework applying the distinction between the two types of economic adaptation to stakeholder theory.

The authors argue that the idea of cooperative adaptation is particularly useful for describing the firm’s collaboration with primary stakeholders in the joint value creation process. In contrast, autonomous adaptation is more relevant for firms interacting with secondary stakeholders who are not directly engaged in joint value creation and may not have formal contractual relationships with the firm. Accordingly, cooperative adaptation can be seen as vital for resolving team production problems affecting joint value creation, whereas autonomous adaptation addresses how the firm maintains legitimacy within the larger stakeholder environment.

Similar to its significance for transaction cost economics, the distinction between the two types of adaptation equips stakeholder theory with a new systematic understanding of a potentially broad spectrum of firm–stakeholder collaboration forms.

This study aims to examine the effect of Industry 4.0 technology on resilience in established cross-border supply chain(s) (SC).

A literature review provides insight into the resilience capabilities of cross-border SC. The research uses a case study of operational international SC: the producers, importers, logistics companies and UK Government (UKG) departments. Semi-structured interviews determine the resilience capabilities and approaches of participants within cross-border SC and how implementing an Industry 4.0 Internet of Things (IoT) and capitals Distributed Ledger (blockchain) based technology platform changes SC resilience capabilities and approaches.

A blockchain-based platform introduces common assured data, reducing data duplication. When combined with IoT technology, the platform improves end-to-end SC visibility and information sharing. Industry 4.0 technology builds collaboration, trust, improved agility, adaptability and integration. It enables common resilience capabilities and approaches that reduce the de-coupling between government agencies and participants of cross-border SC.

The case study presents challenges specific to UKG’s customs border operations; research needs to be repeated in different contexts to confirm findings are generalisable.

Operational SC and UKG customs and excise departments must align their resilience strategies to gain full advantage of Industry 4.0 technologies.

Case study research shows how Industry 4.0 technology reduces the de-coupling between the SC and UKG, enhancing common resilience capabilities within established cross-border operations. Improved information sharing and SC visibility provided by IoT and blockchain technologies support the development of resilience in established cross-border SC and enhance interactions with UKG at the customs border.

This research integrates maintenance planning and production scheduling from a green perspective to reduce the carbon footprint.

A mixed-integer nonlinear programming (MINLP) model is developed to study the relation between production makespan, energy consumption, maintenance actions and footprint, i.e. service level and sustainability measures. The speed scaling technique is used to control energy consumption, the capping policy is used to control CO2 footprint and preventive maintenance (PM) is used to keep the machine working in healthy conditions.

It was found that ignoring maintenance activities increases the schedule makespan by more than 21.80%, the total maintenance time required to keep the machine healthy by up to 75.33% and the CO2 footprint by 15%.

The proposed optimization model can simultaneously be used for maintenance planning, job scheduling and footprint minimization. Furthermore, it can be extended to consider other maintenance activities and production configurations, e.g. flow shop or job shop scheduling.

Maintenance planning, production scheduling and greenhouse gas (GHG) emissions are intertwined in the industry. The proposed model enhances the performance of the maintenance and production systems. Furthermore, it shows the value of conducting maintenance activities on the machine's availability and CO2 footprint.

This work contributes to the literature by combining maintenance planning, single-machine scheduling and environmental aspects in an integrated MINLP model. In addition, the model considers several practical features, such as machine-aging rate, speed scaling technique to control emissions, minimal repair (MR) and PM.

This final chapter of this comprehensive volume serves as a pivotal culmination, offering profound insights into the multifaceted realm of family planning, with a dedicated focus on empowering marginalized communities and advancing sustainable development. Drawing from lessons learned across diverse Asian contexts, this chapter encapsulates the critical importance of family planning as a catalyst for broader development outcomes. It underscores the empowerment of marginalized communities, integrating access to healthcare, education, economic opportunities, and gender equity as central pillars. Furthermore, this chapter delves into the unique lessons derived from the experiences of Bangladesh, a nation exemplifying remarkable strides in family planning. It also emphasizes the significance of context-specific policies, programs, and cross-country collaborations. This book’s concluding chapter presents forward-looking directions for holistic approaches, inclusivity, data-driven decision-making, partnerships, youth engagement, climate resilience, and more. This chapter not only consolidates this book’s invaluable findings but also paves the way for a future where family planning becomes an even more integral part of sustainable development.

The purpose of this article is to solve the issue that apple-picking robots are easily interfered by branches or other apples near the target apple in an unstructured environment, leading to grasping failure and apple damage.

This study introduces the system units of the apple-picking robot prototype, proposes a method to determine the apple-picking direction via 3D point cloud data and optimizes the path planning method according to the calculated picking direction.

After the field experiments, the average deviation of the calculated picking direction from the desired angle was 11.81°, the apple picking success rate was 82% and the picking cycle was 11.1 s.

This paper describes a picking control method for an apple-picking robot that can improve the success and reliability of picking in an unstructured environment and provides a basis for automated and mechanized picking in the future.