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This paper aims to explore the relationship between prudence in risk attitudes and patience of time preference of Chinese apple growers regarding off-farm cold storage of production and marketing in non-harvest seasons. The authors also consider the effect of farmer participation in cooperative-like organizations known as Farm Bases (FBs).

The authors use multiple list methods and elicitation strategies to measure Chinese apple farmers' risk attitudes and time preferences. Because these farmers can either sell their apples immediately to supermarkets or intermediaries or place them in storage, the authors assess correlations between their storage decisions and their preferences regarding risk and time. The authors also differentiate risks involving gains and losses and empirically examine individual risk attitudes in different scenarios.

Marketing decisions are moderately associated with risk attitudes but not time preference. Farmers with memberships in local farmer cooperatives are likely to speculate more in cold storage. Thus, risk aversion behavioral and psychological motives affect farmers' decision-making of cold storage and intertemporal marketing activities. However, membership in cooperatives does not always result in improved income and welfare for farmers.

The research confirms that behavioral factors may strongly drive vulnerable smallholder farmers to speculate into storage even under seasonal and uncertain marketing volatility. There is the need to think deeper about the rationale of promoting cooperatives and other agricultural forms, because imposing these without careful consideration can have negative impacts.

Do risk and time preferences affect the decision of farmers to utilize storage facilities? This question is important because it is not clear if and how risk preferences affect the tradeoff between consuming today and saving for tomorrow, especially for farmers in developing countries.

A quantitative theoretical model is proposed to measure how productivity performance can be affected by strategic decisions related to specific competitive priorities.

This study proposes the Primary Transformation Model (PTM) and an equation to measure cause-and-effect relationships between productivity and competitive priorities.

The interdependence between productivity and competitive priorities was studied using the PTM and the proposed model indicates that strategies that improve external performance also impact internal productivity. It was also observed that the compatibility between competitive priorities depends on the initial manufacturing conditions and the implementation method adopted.

The proposed model is theoretical and, as such, is an abstraction of reality and does not consider all possible aspects. It consists of a novel approach that still requires further empirical testing. The PTM provides insights about the trade-offs between productivity and strategic objectives, as well, contributes to the ongoing research on manufacturing strategy and can be further developed in future studies.

The main practical implication is to allow companies to relate their strategic decisions to their productivity performance.

This research also contributes to societal issues by enabling firms to better align strategic objectives and operations, which ultimately allows offering products more suited to the needs of customers, thus making better use of the required resources and favoring economic growth.

The model proposed allows objective assessment of actions aiming at operational efficiency and effectiveness, in addition to providing insights into cause-and-effect relationships between productivity and competitive priorities. The model can also be used in empirical investigations on manufacturing strategy.

Minimizing the impact on the surrounding environment and maximizing the use of production raw materials while ensuring that the relevant processes and services can be delivered within the specified time are the contents of enterprise supply chain management in the green financial system.

With the continuous development of China's economy and the continuous deepening of the concept of sustainable development, how to further upgrade the enterprise supply chain management is an urgent need to solve. How to maximize the utilization of resources in the supply chain needs to be realized from the whole process of raw material purchase, transportation and processing.

It was proved that digital twin technology had a partial intermediary role in the role of supply chain big data analysis capability on corporate finance, market, operation and other performance.

This paper focused on describing how digital twin technology could be applied to big data analysis of enterprise supply chain under the green financial system and proved its usability through experiments. The experimental results showed that the indirect effect of the path big data analysis capability digital twin technology enterprise financial performance was 0.378. The indirect effect of the path big data analysis capability digital twin technology enterprise market performance was 0.341. The indirect effect of the path big data analysis capability digital twin technology enterprise operational performance was 0.374.

This paper aims to propose a simulation model integrated with an empirical regression analysis to provide a new mathematical formulation for automated storage and retrieval system (AS/RS) travel time estimation under class-based storage and different input/output (I/O) point vertical levels.

A simulation approach is adopted to compute the travel time under different warehouse scenarios. Simulation runs with several I/O point levels and multiple shape factor values.

The proposed model is extremely precise for both single command (SC) and dual command (DC) cycles and very well fitted for a reliable computation of travel times.

The proposed mathematical formulation for estimating the AS/RS travel time advances widely applied methodologies existing in literature. As well as, it provides a practical implication by supporting faster and more accurate travel time computations for both SC and DC cycles. However, the regression analysis is conducted based on simulated data and can be refined by numerical values coming from real warehouses.

This work provides a new simulation model and a refined mathematical equation to estimate AS/RS travel time.

Au stud bump bonding technology is an effective means to realize heterogeneous integration of commercial chips in the 2.5D electronic packaging. The purpose of this paper is to study the long-term reliability of the Au stud bump treated by four different high temperature storage times (200°C for 0, 100, 200 and 300 h).

The bonding strength and the fracture behavior are investigated by chip shear test. The experiment is further studied by microstructural characterization approaches such as scanning electron microscope, energy dispersive spectrometer and so on.

It is recognized that there were mainly three typical fracture models during the chip shear test among all the Au stud bump samples treated by high temperature storage. For solder bump before aging, the fracture occurred at the interface between the Cu pad and the Au stud bump. As the aging time increased, the fracture mainly occurred inside the Au stud bump at 200°C for 100 and 200 h. When aging time increased to 300 h, it is found that the fracture transferred to the interface between the Au stud bump and the Al Pad.

In addition, the bonding strength also changed with the high temperature storage time increasing. The bonding strength does not change linearly with the high temperature storage time increasing but decreases first and then increases. The investigation shows that the formation of the intermetallic compounds because of the reaction between the Au and Al atoms plays a key role on the bonding strength and fracture behavior variation.

The purpose of this study is to examine the effects of inclination angle on the thermal energy storage capability of a phase change material (PCM) within a disc-shaped container. Different container materials are also tested such as plexiglass and aluminium. This study aims to assess the energy storage capacity, melting behaviour and temperature distributions of PCM with a specific melting range (22°C–26°C) for various governing parameters such as inclination angles, aspect ratios (AR) and temperature differences (ΔT) and compare the melting behaviour and energy storage performance of PCM in aluminium containers to those in plexiglass containers.

A finite volume approach was adopted to evaluate the thermal energy storage capability of PCMs. Five inclination angles ranging from 0° to 180° were considered and the energy storage capacity. Also, the melting behaviour of the PCM and temperature distributions of the container with different materials were tested. Two different AR and ΔT values were chosen as parameters to analyse for their effects on the melting performance of the PCM. Conjugate heat transfer problem is solved to see the effects of conduction mode of heat transfer.

The results of the study indicate that as AR decreases, the effect of the inclination angles on the energy storage capacity of the PCM decreases. For lower ΔT, the difference between the maximum and minimum stored energies was 20.88% for AR = 0.20, whereas it was 6.85% for AR = 0.15. Furthermore, under the same conditions, the PCM stored 8.02% more energy in plexiglass containers than in aluminium containers.

This study contributes to the understanding of the influence of inclination angle, container material, AR and ΔT on the thermal energy storage capabilities of PCM in a novel designed container. The findings highlight the importance of AR in mitigating the effect of the inclination angle on energy storage capacity. Additionally, comparing aluminium and plexiglass containers provides insights into the effect of container material on the melting behaviour and energy storage properties of PCM.

Cloud computing services gained huge attention in recent years and many organizations started moving their business data traditional server to the cloud storage providers. However, increased data storage introduces challenges like inefficient usage of resources in the cloud storage, in order to meet the demands of users and maintain the service level agreement with the clients, the cloud server has to allocate the physical machine to the virtual machines as requested, but the random resource allocations procedures lead to inefficient utilization of resources.

This thesis focuses on resource allocation for reasonable utilization of resources. The overall framework comprises of cloudlets, broker, cloud information system, virtual machines, virtual machine manager, and data center. Existing first fit and best fit algorithms consider the minimization of the number of bins but do not consider leftover bins.

The proposed algorithm effectively utilizes the resources compared to first, best and worst fit algorithms. The effect of this utilization efficiency can be seen in metrics where central processing unit (CPU), bandwidth (BW), random access memory (RAM) and power consumption outperformed very well than other algorithms by saving 15 kHz of CPU, 92.6kbps of BW, 6GB of RAM and saved 3kW of power compared to first and best fit algorithms.

The proposed multi-objective bin packing algorithm is better for packing VMs on physical servers in order to better utilize different parameters such as memory availability, CPU speed, power and bandwidth availability in the physical machine.

The purpose of this study is to determine the viability of Lacticaseibacillus rhamnosus GR-1 (L. rhamnosus GR-1) in five yogurt samples with or without quinoa, chickpea, soybean and rice flour over various fermentation periods and refrigerated storage durations, with a focus on exploring the potential of functional foods, which provide health benefits beyond nutritional value. Additionally, the study aimed to evaluate consumer acceptance of yogurt fortified with functional flour. Using a nine-point hedonic scale, from 1 (dislike extremely) to 9 (like extremely), participants rated appearance, flavour, texture and overall acceptability.

The samples were inoculated with the probiotic strain L. rhamnosus GR-1 and fermented for 0, 2, 4 and 6 h at 38°C, followed by refrigerated storage at 4°C for 1, 15 and 30 days, respectively. Microbial enumeration was performed throughout fermentation and storage to assess the viability of L. rhamnosus GR-1. A sensory evaluation involving 86 participants was conducted to assess the consumer acceptability of the yogurt samples.

Notably, L. rhamnosus GR-1 achieved viable counts of 108 colony-forming units per mL in all treatments at all fermentation time points. Over the 30-day storage period, no statistically significant differences (p < 0.05) in average pH values were observed among the five treatments, and within each treatment, pH levels remained stable, with an overall mean of 4.2 ± 0.64. Treatment 4, which featured rice flour fortification, received higher hedonic scores from sensory panellists in terms of appearance, flavour, texture and overall acceptability. These findings indicate that incorporating functional flours in conjunction with cow’s milk effectively promotes and preserves the viability of L. rhamnosus GR-1 in yogurt.

Exploring the potential of probiotic yogurt enriched with diverse functional flours to enhance nutritional content and health benefits as well as attract new consumers, this study addressed a critical gap in understanding consumer perceptions and generated insights for creating innovative and health-promoting dairy products.

The primary objective of this article is to examine current procurement, inventory control and management practices in modern healthcare, with a particular focus on the procurement and management of surgical supplies in a prominent public, highly specialized healthcare sector.

This study was conducted in three phases. In Phase 1, the study team interacted with various hospital management stakeholders, including the surgical hospital store, examined the current procurement process and identified challenges. Phase 2 focused on selecting items for a detailed study and collected the qualitative and quantitative details of the store department of the healthcare sector chosen. A detailed study analyzed revenue, output/demand, inventory levels, etc. In Phase 3, a decision-making framework is proposed, and inventory control systems are redesigned and demonstrated for the selected items.

It was observed that the demand for many surgical items had increased significantly over the years due to an increase in disposable/disposable items, while inventories fluctuated widely. Maximum inventory levels varied between 50 and 75%. Storage and availability were important issues for the hospital. It is assumed the hospital adopts the proposed inventory control system. In this case, the benefits can be a saving of 62% of the maximum inventory, 20% of the average stock in the system and optimal use of storage space, improving the performance and productivity of the hospital.

This study can help the healthcare sector administration to develop better systems for the procurement and delivery of common surgical items and efficient resource allocation. It can help provide adequate training to store staff. This study can help improve management/procurement policies, ordering and delivery systems, better service levels, and inventory control of items in the hospital business context. This study can serve as a pilot study to further investigate the overall hospital operations.

This study can help the healthcare sector administration develop better systems for procuring and delivering common surgical items and efficient resource allocation. It can help provide adequate training to store staff. This study can help improve management/procurement policies, ordering and delivery systems, better service levels and inventory control of items in the hospital business context. This study can serve as a pilot study to further investigate the overall hospital operations.

This study is an early attempt to develop a decision framework and inventory control system from the perspective of healthcare inventory management. The gaps identified in real hospital scenarios are investigated, and theoretically based-inventory management strategies are applied and proposed.

Globally, consumer’s inclination towards functional foods had noticed due to their greater health consciousness coupled with enhanced health-care cost. The fact that probiotics could promote a healthier gut microbiome led projection of probiotic foods as functional foods and had emerged as an important dietary strategy for improved human health. It had established that ice cream was a better carrier for probiotics than fermented milked due to greater stability of probiotics in ice cream matrix. Global demand for ice cream boomed and probiotic ice cream could have been one of the most demanded functional foods. The purpose of this paper was to review the technological aspects and factors affecting probiotic viability and to standardize methodology to produce functional probiotic ice cream.

Attempt was made to search the literature (review and researched papers) to identify diverse factors affecting the probiotic viability and major technological challenge faced during formulation of probiotic ice cream. Keywords used for data searched included dairy-based functional foods, ice cream variants, probiotic ice cream, factors affecting probiotic viability and health benefits of probiotic ice cream.

Retention of probiotic viability at a level of >10⁶ cfu/ml is a prerequisite for functional probiotic ice creams. Functional probiotic ice cream could have been produced with the modification of basic mix and modulating technological parameters during processing and freezing. Functionality can be further enhanced with the inclusion of certain nutraceutical components such as prebiotics, antioxidant, phenolic compounds and dietary fibres. Based upon reviewed literature, suggested method for the manufacture of functional probiotic ice cream involved freezing of a probiotic ice cream mix obtained by blending 10% probiotic fermented milk with 90% non-fermented plain ice cream mix for higher probiotic viability. Probiotic ice cream with functional features, comparable with traditional ice cream in terms of technological and sensory properties could be produced and can crop up as a novel functional food.

Probiotic ice cream with functional features may attract food manufacturers to cater health-conscious consumers.