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Grocery sellers that have entered the online business must now carry out order fulfilment activities previously done by the customer. Consequently, in a context of online sales growth, the purpose of this study is to identify and implement best practices in order to redesign the order picking process in a retailer with a store-based model.

To identify different work alternatives, an approach is developed to analyse the methods used in distinct stores of one large Spanish grocer. The methodology employed is a three-step statistical analysis that combines ANOVA and MANOVA techniques to settle on the best alternatives in each case.

Substantial improvements can be achieved by analysing the different working methods. The three-step statistical analysis identified best practices in terms of their impact on preparation time, allowing a faster working method.

To manage business processes efficiently, online grocers that operate store-based fulfilment strategies can redesign their working method using a criterion based on their own performance.

This is one of the few contributions focusing on the improvement of e-grocery fulfilment operations by disseminating best practices through decision-making criteria. This study contributes by addressing the lack of approaches studying the order picking process by considering its various features and applying best practices.

This paper describes the process of creating a retail ordering application and aims to see how to achieve this through an IDE (integrated development environment) and back-end services for smart cities. The main goals are: allow a user to create an account, allow an admin user to edit or delete an order, create a database of products, test the application and replace the current ordering system, such as a desktop-based application, with a mobile-first approach.

Based on the Scrum method, this paper tries to develop the retail ordering application that can be used on an iOS device, such as an iPhone. Before the application design, the issues related to the software design will be researched and justified.

The proposed application has been created, and the objectives which were proposed have been met in terms of creating a user account and registering it with the database, using this to log in to the application, creating orders by taking the customer and product details and been able to view and edit these through another admin account for smart cities.

For customers, the mobile-based ordering system makes their shopping experience more convenient and easier. For the business, the staff's work can be more efficient, and companies are able to reduce their expenses. For the new software developers, this work demonstrated the process of creating a retail ordering application from scratch.

This work will be of great value to the customers, retail business as well as the new software developers. In order to establish sustainable cities and provide high-quality life to the citizens, the concept of “smart” has been widely used in urban construction. This paper contributes to the smart city area by creating a retail ordering application based on the iOS system.

In online digital spaces, the public/private distinction is challenged in many different ways. The purpose of this paper is to show that the normative order of the internet is a suitable lens through which the complex relationship of private and public norms and their impact on communication spheres and today’s and tomorrow’s dynamic public can be understood.

Habermas’ conception of the public sphere provides us with the ideal starting point for our normative analysis of German court cases concerning the application of public law in privately-owned online communication spaces. The normative analysis allows us to pose an important theoretical question regarding the necessity and circumstances of a codification of a (private) online order.

This research paper shows that a reconsideration of the Kantian theory enables the transcendental constitution of normativity – and of new publics, is necessary because normativity that learns from its environment can no longer be described by referring to traditional categories of, and criteria for, subjectivity. The research paper shows that the normative order of the internet is based on and produces a liquefied system characterized by self-learning normativity.

This paper offers a unique perspective on the norm building process in privately-owned online communication spaces and poses an important theoretical question that helps to better understand the emerging normative orders, the shift in our view on “publics” and offers a useful analytical tool for a better explain, predict and legitimize the creation of new order-internal norms.

The main purpose of this research is to investigate acceptability of different delivery methods in e-grocery (home delivery, pick-up from store, pick-up from locker) and the respective willingness of customers to pay for them using a stated preference ranking experiment.

Data collected involved two countries (Greece and UK) with different level of e-grocery development and two different distribution conditions (weekly and urgent order). Rank-ordered logit model is used to analyse the ranking experiment and calculate the willingness-to-pay (WTP) measures. Delivery mode, cost and time window are used as independent variables.

Results indicated that home delivery and picking-up from locker appear to be clearly preferable than picking-up from store. However, home delivery seems to hold a stronger competitive position over the other delivery methods, especially in the weekly order and in the UK market. The pick-up from locker option appears to be a competitive delivery mode for consumers who are cost sensitive and shop under urgent conditions. Willingness to use and pay for picking-up from locker increases significantly in the context of same-day delivery.

The information provided in this study will help retailers to design and implement distribution schemes that can meet consumers' preferences for e-grocery. WTP differences among the consumer groups and the distribution conditions examined can have a considerable impact on the evaluation of marketing and pricing strategies applied by e-retailers.

Consumer preference and the respective WTP for different delivery methods in e-grocery, especially for the pick-up from locker option, have not been systematically investigated.

This paper's purpose is to suggest that manufacturers strategically place soft orders for assembly materials with suppliers in Silk Road Economic Belt countries who probably doubt the realization of the soft orders placed.

First, a two-stage Stackelberg competition is constructed, taking into account the supplier's trust level in formulating the decision process in the assembly supply chain. The authors then provide a buyback contract to coordinate the supply chain, in which the manufacturer obtains enough supplies by sharing some of the perceived risks of not fully trusted suppliers. Furthermore, the authors conduct a numerical study to investigate the influence of trust under a decentralized case and a buyback contract.

The authors found that all supply chain partners in Silk Road Economic Belt countries experience potential losses due to not fully trusting certain conditions. The study also shows that, in Silk Road Economic Belt countries, operating under a buyback contract is better than being without one in terms of assembly supply chain performance.

On the one hand, the authors only consider the asymmetry of demand information without considering that of cost structure information. On the other hand, a natural extension of the paper is to integrate single-period transactions into the multi-period transaction problem setting. As all these issues require substantial effort, the authors reserve them for future exploration.

Doing business with not-fully-trustworthy partners in Silk Road Economic Belt countries is risky, and this study reveals how trust works in global cooperation and with strategic reactions in situations of partial trust.

Recent studies have highlighted the importance of adopting a contingency approach to configuring omnichannel warehouses. Nonetheless, research on how various contextual factors influence the selection of warehouse configuration is scarce. This study fills this knowledge gap by exploring how and why certain configurations fit in different omnichannel contexts.

A case study is conducted with six leading Swedish omnichannel retailers. Focusing on outbound warehouse configurations, data are collected through interviews, on-site observations, and secondary sources. A multistep analysis is made, including both pattern matching and explanation building.

The qualitative analysis reveals 16 contextual factors, of which assortment range, requested online order fulfillment times, goods size and total transactions are the most influential. The study shows how contextual factors create different challenges, thereby influencing the choice of the configurations. In addition to market dynamics and task complexity, the study describes four categories of the factors and related challenges that are particularly important in omnichannels: speed, space, economies of scale and tied-up capital.

The findings highlight the importance of understanding context and imply that multiple challenges may require trade-offs when selecting configurations, for example, regarding what storage, processes and resources to integrate or separate. To confirm, extend, challenge and further operationalize the ideas and observations put forward in this paper, an agenda with future research issues is given for this accelerating, contemporary phenomenon.

Managers could leverage the frameworks proposed for the contextual profiling of their current and future positions. The frameworks provide support for understanding the important challenges and potential trade-offs and developing aligned configurations.

This study is original in the way it provides in-depth, case study findings about contextual factors and their influence on omnichannel warehouse configuration.

The purpose of this study is threefold: (1) to propose partial least squares path modeling (PLS-PM) as a way to estimate models containing composites of composites and to compare the performance of the PLS-PM approaches in this context, (2) to provide and evaluate two testing procedures to assess the overall fit of such models and (3) to introduce user-friendly step-by-step guidelines.

A simulation is conducted to examine the PLS-PM approaches and the performance of the two proposed testing procedures.

The simulation results show that the two-stage approach, its combination with the repeated indicators approach and the extended repeated indicators approach perform similarly. However, only the former is Fisher consistent. Moreover, the simulation shows that guidelines neglecting model fit assessment miss an important opportunity to detect misspecified models. Finally, the results show that both testing procedures based on the two-stage approach allow for assessment of the model fit.

Analysts who estimate and assess models containing composites of composites should use the authors’ guidelines, since the majority of existing guidelines neglect model fit assessment and thus omit a crucial step of structural equation modeling.

This study contributes to the understanding of the discussed approaches. Moreover, it highlights the importance of overall model fit assessment and provides insights about testing the fit of models containing composites of composites. Based on these findings, step-by-step guidelines are introduced to estimate and assess models containing composites of composites.

By mobilizing the empirical setting of a megaproject, this study problematizes public budgeting as participatory practice. The authors suggest that megaprojects are prone to democratic legitimacy challenges due to a long history of cost overruns, which provides stakeholders with a chance to dramatize a budgetary controversy.

Through article and document data, the authors reconstructed a controversy that emerged around the budget of Stockholm/Åre’s candidature for the Olympic Winter Games 2026. The authors used Boltanski and Thévenot's (2006) orders of worth to systematically analyze the justification work of key stakeholder groups involved in the controversy.

This study illustrates that a budgetary controversy was actively maintained by stakeholder groups, which resulted in a lack of public support and the eventual demise of the Olympic candidature. As such, the authors provide a more nuanced understanding of public budgeting as a controversy-based process vis-à-vis a wider public with regard to the broken institution of megaprojects.

This study suggests more attention to the disruptive power of public scrutiny and the dramatization of budgeting in megaprojects. In this empirical case, the authors show how stakeholders tend to take their technical concerns too far in order to challenge a budget, even though megaprojects generally provide an ill-suited setting for accurate forecasts.

While studies around the financial legacies of megaprojects have somewhat matured, very few have looked at pitching them. However, the authors argue that megaprojects are increasingly faced with financial skepticism upon their approval upfront.

The purpose of this paper is to derive the analytical expression of fractional order reducing generation operator (or inverse accumulating generating operation) and study its properties.

This disaggregation method includes three main steps. First, by utilizing Gamma function expanded for integer factorial, this paper expands one order reducing generation operator into integer order reducing generation operator and fractional order reducing generation operator, and gives the analytical expression of fractional order reducing generation operator. Then, studies the commutative law and exponential law of fractional order reducing generation operator. Lastly, gives several examples of fractional order reducing generation operator and verifies the commutative law and exponential law of fractional order reducing generation operator.

The authors pull the analytical expression of fractional order reducing generation operator and verify that fractional order reducing generation operator satisfies commutative law and exponential law.

Expanding the reducing generation operator would help develop grey prediction model with fractional order operators and widen the application fields of grey prediction models.

The analytical expression of fractional order reducing generation operator, properties of commutative law and exponential law for fractional order reducing generation operator are first studied.

Order picking in a warehouse consumes most of the stockroom labour because of the high frequency of transactions. This article presents an algorithm for order picking in narrow‐aisle warehouses and describes its implementation using a spreadsheet. The algorithm is illustrated by an example, and the algorithmic method is compared with the current method of order picking in the food industry. Randomly generated problems show savings of up to 85 per cent in distance travelled by the pick‐up vehicle. The manager of the warehouse, where the method has been implemented, confirmed that he has become more effective and efficient on order delivery by using it.