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Recently emerged Packaging-as-a-Service (PaaS) systems adopt aspects of access-based services and triadic frameworks, which have typically been treated as conceptually separate. The purpose of this paper is to investigate the implications of blending the two in what we call “access-based triadic systems,” by empirically evaluating intentions to adopt PaaS systems for takeaway food among restaurants and consumers.

We derived relevant attributes of PaaS systems from a qualitative pre-study with restaurants and consumers. Next, we conducted two factorial survey experiments with restaurants (N = 176) and consumers (N = 245) in Germany to quantitatively test the effects of those system attributes on their adoption intentions.

This paper highlights that the role of access-based triadic system providers as both the owners of shared assets and the operators of a triadic system is associated with a novel set of challenges and opportunities: System providers need to attract a critical mass of business and end customers while balancing asset protection and system complexity. At the same time, asset ownership introduces opportunities for improved quality control and differentiation from competition.

Conceptually, this paper extends research on access-based services and triadic frameworks by describing an unexplored hybrid form of non-ownership consumption we call “access-based triadic systems.” Empirically, this paper addresses the need to account for the demands of two distinct target groups in triadic systems and demonstrates how factorial survey experiments can be leveraged in this field.

This study aims to focus on understanding how different jet angles and Reynolds numbers influence the phase change materials’ (PCMs) melting process and their capacity to store energy. This approach is intended to offer novel insights into enhancing thermal energy storage systems, particularly for applications where heat transfer efficiency and energy storage are critical.

The research involved an experimental and numerical analysis of PCM with a melting temperature range of 22 °C–26°C under various conditions. Three different jet angles (45°, 90° and 135°) and two container angles (45° and 90°) were tested. Additionally, two different Reynolds numbers (2,235 and 4,470) were used to explore the effects of jet outlet velocities on PCM melting behaviour. The study used a circular container and analysed the melting process using the hot air inclined jet impingement (HAIJI) method.

The obtained results showed that the average temperature for the last time step at Ф = 90° and Re = 4,470 is 6.26% higher for Ф = 135° and 14.23% higher for Ф = 90° compared with the 45° jet angle. It is also observed that the jet angle, especially for Ф = 90°, is a much more important factor in energy storage than the Reynolds number. In other words, the jet angle can be used as a passive control parameter for energy storage.

This study offers a novel perspective on the effective storage of waste heat transferred with air, such as exhaust gases. It provides valuable insights into the role of jet inclination angles and Reynolds numbers in optimizing the melting and energy storage performance of PCMs, which can be crucial for enhancing the efficiency of thermal energy storage systems.

This empirical study explores the profound impact of management functions on the productivity of yard cargo handling equipment within container terminals.

By closely examining crucial management aspects such as planning, organizing, leading, and controlling, a comprehensive managerial behavior framework was developed through focus group studies (FGS) and focal interviews. These qualitative methods were complemented by the distribution of questionnaires to practitioners in Vietnam. To validate the concept of management functions and analyze their influence on effective management practices for equipment efficiency, a structural equation model (SEM) technique was employed using partial least-squares estimation (PLS).

The findings of this study demonstrate that planning (PL), organizing (OR), and controlling (CT) significantly contribute to the productivity of yard cargo handling equipment, while leading (LD) does not exhibit a direct positive impact.

Theoretically, this study contributes by providing clarity to the definition, purpose, and value of management functions in the field of cargo handling equipment management. Furthermore, these research findings offer valuable insights to terminal operators and managers, enabling them to optimize their management strategies and enhance productivity levels, ultimately resulting in improved operational outcomes.

This study adopted the collaborative consumption triangle to explore the influence of online food delivery platforms (OFDP) on consumer purchase intentions. It investigates the effects of restaurants' corporate social responsibility (CSR) practices, individuals' food neophilic tendencies (FNT), and platforms' perceived benefits on purchase intention within OFDP. Furthermore, the study analyses differences in consumers' pro-environmental behaviour (PEB) on OFDP.

The 497 participants conducted a web-based self-completion survey, using structural equation modelling to analyse the path structure of consumer purchasing intention. Furthermore, differences in PEB among OFDP consumers were compared through multigroup analysis.

The findings indicate that CSR influences the perceived value of sustainability and that the perceived value of sustainability influences purchase intention. Additionally, the influence of the perceived value of sustainability on purchase intention is more pronounced among consumers with low PEB compared to those with high PEB.

The findings may not be generalisable to other countries due to cultural differences, CSR policies, and strategies for promoting sustainable development.

The study provides valuable contributions related to (1) restaurants increasing their revenue and meeting their long-term sustainable development goals; (2) providing reusable containers policy and reusable containers policy and category tags for restaurants within OFDP.

This study is a pioneering work examining factors influencing purchase intentions within OFDP from the tripartite collaborative consumption perspective post-COVID-19 and focuses on the differences in PEB concerning OFDP.

This paper aims to propose a robust method for non-rigid point set registration, using the Gaussian mixture model and accommodating non-rigid transformations. The posterior probabilities of the mixture model are determined through the proposed integrated feature divergence.

The method involves an alternating two-step framework, comprising correspondence estimation and subsequent transformation updating. For correspondence estimation, integrated feature divergences including both global and local features, are coupled with deterministic annealing to address the non-convexity problem of registration. For transformation updating, the expectation-maximization iteration scheme is introduced to iteratively refine correspondence and transformation estimation until convergence.

The experiments confirm that the proposed registration approach exhibits remarkable robustness on deformation, noise, outliers and occlusion for both 2D and 3D point clouds. Furthermore, the proposed method outperforms existing analogous algorithms in terms of time complexity. Application of stabilizing and securing intermodal containers loaded on ships is performed. The results demonstrate that the proposed registration framework exhibits excellent adaptability for real-scan point clouds, and achieves comparatively superior alignments in a shorter time.

The integrated feature divergence, involving both global and local information of points, is proven to be an effective indicator for measuring the reliability of point correspondences. This inclusion prevents premature convergence, resulting in more robust registration results for our proposed method. Simultaneously, the total operating time is reduced due to a lower number of iterations.

Non-profit organizations (NPOs) are exposed to a highly competitive environment in which they are forced to grow their commercial activity to acquire additional financial resources. This study aims to create an understanding of how NPOs involved in textile reuse as a revenue-generating programme manage their reverse supply chains (RSC).

The research involves an embedded single-case study of NPOs in Finland involved in post-use textile collection. The main data sources are semi-structured interviews and participant observations.

This study is inspired by the microfoundations movement and identifies the underlying microfoundations of the NPOs’ capabilities for managing RSC for textile reuse. The study contributes to the literature by demonstrating NPOs’ lower-level, granular practices and their adaptations for achieving quality outcomes in textile reuse.

The findings have context sensitivity and apply to the NPOs which operate in a context similar to Finland, such as in other Nordic countries.

This study continues the discussion on the adoption of “business-like” practices in the NPOs’ pursuit of additional revenue streams to finance humanitarian work. The findings of this study can also be transferred to the growing area of domestic textile circularity.

Using the case of NPOs in textile reuse, the study illustrates how RSC management can serve a social, non-profit cause and transform unwanted textile products into a source of fundraising for humanitarian work.

This enriches the understanding of NPOs’ practices within the scope of revenue-generating programmes by examining one of them – textile reuse through charity shops from an RSC perspective.

Money laundering (ML) is a major criminal offence stemming from unethical practices by personnel on the ground at Chattogram Port, an important import and export facility in Bangladesh. Because money can be more easily laundered through imports, it is necessary to investigate the dubious process in this sector. This study aims to identify the items most regularly used for easy ML and the factors contributing to their vulnerability.

This research uses a qualitative approach and analyses information from primary sources. Data is obtained from customs officials, port authority personnel, importers and customs brokers through semi-structured questionnaires. Although there are many techniques for ML, this study only found three most overwhelming: under-invoicing, over-invoicing and misdeclaration. A few case studies have been used based on newspaper reports and the internet to triangulate the qualitative data.

Four import items – food products, garments, capital machinery and chemicals – have a higher risk of ML. This study also revealed that money launderers prefer under-invoicing food and garment items. Misdeclaration is more commonly associated with capital machinery and chemical items. Over-invoicing, on the other hand, is only prevalent in government purchases. The port authorities need to pay particular attention to these issues.

As ML is an ongoing activity that changes over time, the findings of this research are circumscribed by the data collected at a single point in time. Additionally, this research did not consider alternative laundering methods.

The research results can provide a basis for creating effective anti-money laundering (AML) strategies to assist with sustainable economic growth.

Developing effective AML measures can help combat corruption and establish good governance in the country and support human well-being.

This paper presents original research findings based on technical analysis. The Chattogram Port Authority and the National Board of Revenue have accepted and used the main findings in a collaborative action plan to tackle ML. The Bangladesh Bank, the country’s central bank, has also incorporated the necessary guidelines and regulations into the Money Laundering Prevention Act, 2012.

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

This paper proposes a new metric, named Operational Space Efficiency (OpSE), intended to diagnose and quantify the inefficient use of floor space for stocking materials in industrial workstations. OpSE presents a formulation analogous to the well-known Overall Equipment Effectiveness and can be obtained as the product of three distinct indicators: Standard Compliance Effectiveness, Standards Selection Effectiveness and Design Space-usage Effectiveness.

This indicator scrutinizes how usefully floor space in workstations is used to temporarily stock materials in the form of raw materials, semi-finished products, parts and components. It is suited for analyzing fixed-position layouts as well as product layouts typical of repetitive manufacturing settings, such as assembly lines in the automotive sector. The proposed indicator leverages an appropriate loss structure that features those factors affecting floor space utilization in workstations with regard to supplying and stocking materials.

An Italian manufacturer in the field of electro-technology was used as an industrial case study for the application of the methodology. The application shows how the three indicators work in practice, the effectiveness of OpSE and the methodology as a whole, in diagnosing floor space usage inefficiencies and in properly addressing improvement actions of the internal logistics in industrial settings.

The paper scrutinizes some important Key Performance Indicators (KPIs) dealing with space usage efficiency and identifies some significant drawbacks. Then it suggests a new, inclusive structure of losses and a KPI that not only measures efficiency but also allows to identify viable countermeasures.