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Prior literature has widely established that the design of storage locations impacts order picking task performance. The purpose of this study is to investigate the performance impact of unit loads, e.g. pallets or rolling cages, utilized by pickers to pack products after picking them from storage locations.

An empirical analysis of archival data on a manual order picking system for deep-freeze products was performed in cooperation with a German brick-and-mortar retailer. The dataset comprises N = 343,259 storage location visits from 17 order pickers. The analysis was also supported by the development and the results of a batch assignment model that takes unit load selection into account.

The analysis reveals that unit load selection affects order picking task performance. Standardized rolling cages can decrease processing time by up to 8.42% compared to standardized isolated rolling boxes used in cold retail supply chains. Potential cost savings originating from optimal batch assignment range from 1.03% to 39.29%, depending on batch characteristics.

This study contributes to the literature on factors impacting order picking task performance, considering the characteristics of unit loads where products are packed on after they have been picked from the storage locations. In addition, it provides potential task performance improvements in cold retail supply chains.

This research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature logistics centers, with the goal of reducing food loss caused by temperature abuse.

The authors applied ABC clustering to the products in a simulated database of historical orders modeled after the actual order pattern of a large cold logistics company; then, the authors mined the association rules and calculated the sales volume correlation indices of the ordered products. Finally, the authors generated three different simulated order databases to compare order picking time and waiting time of orders in the staging area under eight different storage location assignment strategies.

All the eight proposed storage location assignment strategies significantly improve the order picking time (by up to 8%) and the waiting time of orders in the staging area (by up to 22%) compared with random placement.

The results of this research are based on a case study and simulated data, which implies that, if the best performing strategies are applied to different environments, the extent of the improvements may vary. Additionally, the authors only considered specific settings in terms of order picker routing, zoning and batching: other settings may lead to different results.

A storage location assignment strategy that adopts dispersion and takes into consideration ABC clustering and shipping frequency provides the best performance in minimizing order picker's travel distance, order picking time, and waiting time of orders in the staging area. Other strategies may be a better fit if the company's objectives differ.

Previous research on optimal storage location assignment rarely considered item association rules based on sales volume correlation. This study combines such rules with several storage planning strategies, ABC clustering, and two warehouse layouts; then, it evaluates their performance compared to the random placement, to find which one minimizes the order picking time and the order waiting time in the staging area, with a 30-min time limit to preserve the integrity of the cold chain. Order picking under these conditions was rarely studied before, because they may be irrelevant when dealing with temperature-insensitive items but become critical in cold warehouses to prevent temperature abuse.

The study examines how calculative practices and accountability appear in a rural community of marginalised people in Egypt who depend on jasmine plantations that contribute to the production of global essences.

The data were collected from various sources, namely conversations with villagers, documents and relevant videos and news available on social media and the Internet. This study draws on the concepts of social accountability, the politics of blame avoidance and using calculative practices as a language to explain accountability in context.

The author found a lack of accountability on the part of the government and business owners, with serious implications for the livelihoods of people in a community that has been wholly dependent on jasmine plantations for a century. Power holders have deployed a blame-shifting game to avoid social responsibility. In response, calculative practices rather than advanced accounting tools are used by the poor in the community to induce power holders to be accountable.

The findings of this study show that authorities need to take proactive steps to address the disadvantaged position of powerless people in the lower echelons of society, recognising their accountability for those people.

This paper enhances the understanding of the status of calculative practices and accountability in a community of marginalised people who contribute to the production of global commodities. The paper also enhances the understanding of what goes on behind the scenes with popular and prestigious commodities, whose development is initiated in poor countries, with the end product marketed in rich Western countries.

General Data Protection Regulation (GDPR) of the European Union (EU) was passed to protect data privacy. Though the GDPR intended to address issues related to data privacy in the EU, it created an extra-territorial effect through Articles 3, 45 and 46. Extra-territorial effect refers to the application or the effect of local laws and regulations in another country. Lawmakers around the globe passed or intensified their efforts to pass laws to have personal data privacy covered so that they meet the adequacy requirement under Articles 45–46 of GDPR while providing comprehensive legislation locally. This study aims to analyze the Malaysian and Saudi Arabian legislation on health data privacy and their adequacy in meeting GDPR data privacy protection requirements.

The research used a systematic literature review, legal content analysis and comparative analysis to critically analyze the health data protection in Malaysia and Saudi Arabia in comparison with GDPR and to see the adequacy of health data protection that could meet the requirement of EU data transfer requirement.

The finding suggested that the private sector is better regulated in Malaysia than the public sector. Saudi Arabia has some general laws to cover health data privacy in both public and private sector organizations until the newly passed data protection law is implemented in 2024. The finding also suggested that the Personal Data Protection Act 2010 of Malaysia and the Personal Data Protection Law 2022 of Saudi Arabia could be considered “adequate” under GDPR.

The research would be able to identify the key principles that could identify the adequacy of the laws about health data in Malaysia and Saudi Arabia as there is a dearth of literature in this area. This will help to propose suggestions to improve the laws concerning health data protection so that various stakeholders can benefit from it.

The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.

A visual sweetness scale with an arrow pointing to a specific sweetness level is now required on all labels of AOC Alsace. The sweetness scale makes it easier for consumers to understand what is in the bottle. What is less clear, however, is whether such labeling is always effective. To fill this gap, the current research paper aims to examine the positive and negative effects (double-edged effects) of a visual sweetness scale and identify the boundary condition.

Two studies were conducted using a 2 (cue type: scale vs text) by 2 (consumer type: novices vs experienced wine consumers) between-subjects, quasi-experimental design.

The double-edged effects are only significant among wine novices. Specifically, though wine novices are more likely to purchase wine with a sweetness scale (vs text) due to perceived diagnosticity (Study 1), they are unwilling to pay more due to low perceived quality (Study 2).

The study findings provide practical implications for wine producers, marketers and restaurants regarding when and how to use the sweetness scale on wine labels and wine service.

To the best of the authors’ knowledge, this research is the first to reveal the impact of visualizing wine style on wine labels. More importantly, while most previous research demonstrates the positive effects of using visual cues, this research sheds light on its drawbacks and examines the underlying mechanisms.

Design Science (DS) is a relatively new paradigm for addressing complex real-world problems through the design and evaluation of artifacts. Its constituent methodologies are currently being discussed and established in numerous related research fields, such as information systems and management (Hevner et al., 2004). However, a DS methodology that describes the “how to” is largely lacking, not only in the field of OM but in general. The Theory of Constraints (TOC) and its underlying thinking processes (TP) have produced several novel artifacts for addressing ill-structured real-world operations problems (Dettmer, 1997; Goldratt, 1994), but they have not been analyzed from a DS research standpoint. The purpose of this research is to demonstrate how TOC’s thinking process methodology can be used for conducting exploratory DS research in Operations and Supply Chain Management (OSCM).

A case study of spare parts replenishment illustrates the use of TOC’s thinking processes in DS to structure an initially unstructured problem context and to facilitate the design of a novel solution.

TOC’s thinking processes are an effective methodology for problem-solving DS research, enabling the development of novel solutions in initially unstructured and wicked problem situations. Combined with structured CIMO design logic TOC’s thinking process offers a systematic method for exploring wicked problems, designing novel solutions, and demonstrating theoretical contributions.

The implication for research is that TOC’s thinking process methodology can provide important elements of the lacking “how to” methodology for DS research, not only for the field of OM but in general for the field of management.

The practical outcome of the research is a novel design for dynamic buffer-based replenishment that extends beyond organizational boundaries.

This work shows how the thinking processes can be used in DS research to develop rigorous design propositions for ill-structured problems.

This paper aims to model the price of cellar tours using a hedonic pricing approach. The authors analyze the complex relationship between the price of an add-on (here, cellar tours) and the price of the reference product (here, wine).

Thanks to a large database containing information on about 1,000 winery experiences, the authors regress the price of cellar tours on wine prices and on a broad set of objective characteristics that are (1) tour specific and (2) common to all tours offered by the winery. These exogenous controls include the type and style of experience offered, amenities and winemaking characteristics.

The authors show that the price of cellar tours follows the price of the most expensive wine sold by the winery, which is a proxy for reputation. The authors find that one of the main determinants of cellar tour prices is visit length: wineries charge more for longer experiences. The number of wines tasted during the visit also increases the price. Prices are higher in places where there is a high level of wine tourism activity, which might be a sign of authenticity.

Wine producers in different countries need to gain insights on how to price cellar tours, which are composite goods. The results can help practitioners price their winery experience according to common practices in different wine regions. The results may also be of interest to professionals in the tourism sector who are in charge of the pricing of by-products (e.g. tee-shirts, books, etc.), or for luxury fashion labels extending their brand in the catering industry with cafes and restaurants.

To the best of the authors’ knowledge, this paper is the first empirical analysis that examines the complex relationship between the price of an add-on and the price of the reference product in the context of wine tourism.

This article analyzes the relationships between different conceptions of time, socioeconomic development and cultural values.

We focus on three major aspects of time, namely, 1) duration, 2) orientation and 3) tempo. Furthermore, we draw on modernization theory to distinguish between agrarian/traditional and industrial/modern societies and their respective cultural values.

Analyses indicate that agrarian/traditional societies with cultural values such as collectivism, survival, religiosity and hierarchical structures are marked by subjective/cyclical/inaccurate, past-oriented and slow-paced conceptions of time. In contrast, industrial/modern societies with cultural values such as individualism, self-expression, secularism and egalitarianism are marked by objective/linear/accurate, future-oriented and accelerated conceptions of time.

This paper introduces an original conceptualization of the three dimensions of time – duration, orientation and tempo – previously overlooked in the literature. Additionally, it provides an in-depth and comprehensive analysis of the relationships between time, culture and socioeconomic development.

Construction experts acknowledge the adverse effects of rework on project performance. However, the limited understanding of its underlying causes remains a significant challenge. Therefore, this study aimed to thoroughly investigate the sources of construction rework.

A mixed review using bibliometric analysis as a quantitative method and content analysis as a qualitative method was performed to understand the current knowledge in the field. The Web of Science (WoS) was selected for its comprehensive collection of major research articles and integrated analytical tools for generating representative data. The study involved an extensive bibliometric analysis of 107 journal articles on rework causes from 1991 to 2023. RStudio Bibliometrix, an R statistical programming package, was used to analyze rework origins. This method involved mapping the research landscape, identifying research gaps and analyzing emerging trends.

The causes of rework can be classified into three main clusters: human- and contractual-based rework causes, design-, quality- and project management-based rework causes and organizational-based rework causes.

Although several studies have addressed rework causes from various perspectives and methods, the topic has not been investigated holistically. This study is the first to leverage the quantitative and qualitative analytical capabilities of the RStudio Bibliometrix package. Innovative approaches, including the use of metrics, such as the h-index, thematic mapping and trend topic analysis, were employed for a comprehensive understanding of rework causes.