European Retail Research Articles

Do Firms Proactively Build Internal Markets for Redeployment? Evidence from a Natural Experiment

The topic of related diversification is of fundamental interest to corporate strategy research. However, the understanding of how the potential for resource redeployment might encourage related diversification is limited. This paper explores the impact of the 2006 German real estate transfer tax (RETT) reform, which led to higher RETT rates but retained the exemption from RETT for corporate restructurings. We propose that firms might have reacted strategically to the threat of higher transfer taxes by combining related businesses into a portfolio, providing an efficient internal market for reallocating property assets in the event of business-specific shocks. Consistent with a dynamic perspective on relatedness, difference-in-differences analyses of the European retail market show that the probability of related diversification increased significantly for firms that were affected by the reform, relative to control firms. This finding contributes to the literature that links firm boundary choices to intertemporal economies of scope and offers new insights into the real effects of transfer tax policies. This paper was accepted by Alfonso Gambardella, business strategy. Funding: This work was supported by the Ministerio de Ciencia, Innovación y Universidades [Grant PID2020-115660GB-I00]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.02396 .

National retailing after the Second World War: structural changes, differences and the impact of the socialist model on the Czech and Slovak Republics (1953–1989)

ABSTRACT Changes in retail structures, processes, and culture in post-war Europe were strongly affected by the post-war economic boom, the origin of a mass consumer society, and the adaptation of innovations from the United States. Retail structures and the culture of consumption remained different in the Czech and Slovak parts of the former Czechoslovakia after the Second World War, which influenced the development of retail trade in both countries. After the rise to power of the communists, retail was nationalised, leading to centralising trends in the Czech Republic and decentralisation trends in Slovakia. As a result, the retail structure differed in the two countries. While the Czech Republic showed a preference for larger stores, Slovakia focused more on smaller stores, particularly in rural areas. Although the post-war period brought positive changes, such as the growth of retail trade and the restoration of the population’s purchasing power, the socialist economic model, which was controlled by state-owned enterprises, led to insufficient development and investment in retail and a lack of innovation and efficiency. The post-war period represented a key era for the transformation of European retail; the development trends in post-socialist countries, however, differed from other, capitalist countries.

Is the proliferation of private standards acting as a non-tariff trade barrier in agrifood trade? Evidence from Chilean grape exports

PurposeThe purpose of this paper is to describe and analyze the impacts that the recent proliferation of private and overlapping standards is having in the trade of agricultural products from developing countries.Design/methodology/approachIn a first stage industry experts in the Chilean fresh fruit trading industry were interviewed to understand the perceived impact that private standards are imposing in the industry. These interviews allowed to identify the market case study, table grapes, the landscape of private standards and their prevalence in different countries. In a second stage, a gravity trade model for trade in table grapes was estimated, with a focus on the more stringent countries identified by experts in the first stage.FindingsWe show evidence that the proliferation of private standards required by large European retailers has diverted trade away from more stringent countries that require more certifications (and into less stringent European markets). We also show that the costs of these additional certifications have been shared by trading partners, via an increase in direct sales, as opposed to consignment (the traditional marketing mode), which is associated with higher prices.Research limitations/implicationsThe impacts of the recent proliferation of private and overlapping standards in international trade needs to be better understood both by the legal and economic literature. While the use of private standards has been growing since the 1990s, there is a recent trend of large European retailers imposing their own and overlapping standards that needs to be better understood to inform policy.Originality/valueWhile there is a thin literature on the impact of private standards on trade, most of this has studied the effects of the now de facto mandatory GlobalGAP certification. However, there is a recent trend by large European retailers of demanding their own private certifications, together with other already existing overlapping private standards. This study describes and analyzes the impacts of this rather new trend.

Prediction of customer demand for perishable products in retail inventory management, using the hybrid prophet-XGBoost model during the post-COVID-19 period

ABSTRACT Retail inventory management (IM) presents challenges in decision-making, especially in determining optimal inventory levels for future customer demand alignment. This study focuses on predicting dairy product demand by a significant European retail company using historical order data. As dairy products are perishable and constitute a relevant portion of retail trade volume, accurate IM is crucial to prevent wastage and meet customer needs. However, external factors like COVID-19 may impact demand volatility and seasonal patterns. Given the absence of scientific studies on predicting post-COVID-19 demand, our research aims to fill this gap by proposing alternatives, such as excluding the pandemic period and developing a historical imputation. The study employs two predictive models, Prophet and XGBoost, known for their superior performance in predicting demand. Moreover, a hybrid approach combining both models is proposed to enhance prediction accuracy by leveraging the capacity of the Prophet model to handle seasonal and holiday-period effects and XGBoost’s regularization to prevent overfitting. The results demonstrate the feasibility of historical imputation and the hybrid model approach, improving significantly individual model performance. The principal application of the study is to propose an approach to predict the shipment of other products in a post-COVID-19 context.

Developing The World By Teaching Domestic Consumption: Swiss Supermarkets And The Emergence Of Development Aid Policies In The Early Postwar Period

In the early post-Second World War period, Migros of Switzerland was the first European retail business to adopt the American supermarket model. Its success, however, has not only been a matter of technological and logistical innovation. Migros’ founder, Gottlieb Duttweiler, was convinced that consumer education was part and parcel of a new style of selling consumption. This conviction was at the basis of a strategy entering foreign markets and of exporting the Migros model abroad. Similar to post-World War II economic rehabilitation programs, Duttweiler pursued an indigenous modernization agenda, based on a new principle of “rational consumption”—he did not hesitate to label this as a genuine version of entrepreneurial development aid. Against the backdrop of the establishment of Migros’ activities in Turkey, this article discusses the participation of entrepreneurs in the international development policies after the Second World War. The history of Migros Türk sheds light not only on the entrepreneurial approach to modernization policy, which was often different to that adopted in government programs, but also on how this influenced critical consumerism inside and outside Switzerland over the long term.

The supply of convenience stores: Challenges of short-distance routing within the constraints of working time regulations

Convenience stores are small shops typically located in dense urban areas. They are an important element in modern retailing considering growing urbanization. The layout of convenience stores usually differs significantly for individual stores depending on the local conditions and the types of store (e.g., grocery stores, kiosks, gas stations). Convenience stores have specific delivery requirements that differ significantly due to their variety. In this context, retailers have to cope with small order sizes and frequent deliveries that need to occur within opening hours or predetermined time windows. In addition to these requirements, working hour regulations for the drivers, i.e., the consideration of break times and tour duration restrictions, have to be respected. These regulations have so far been neglected within short-distance routing but significantly impact the planning in practice. The supply of convenience stores is thus a major challenge for retailers.This article addresses the supply of convenience stores as it takes place at a major European retailer. We develop a mathematical model that integrates existing working time regulations and actual requirements in retail practice. The resulting routing problem is solved using an adaptive large neighborhood search. We demonstrate the impact of the requirements imposed on the routing problem and corresponding delivery solutions in numerical studies. Our experiments show that ignoring break times within route planning when strict time windows are given leads to non-feasible solutions and a potential delay in deliveries of more than 18 h for a single planning week.

Learning efficient in-store picking strategies to reduce customer encounters in omnichannel retail

Omnichannel retailers are reinventing stores to meet the growing demand of the online channel. Several retailers now use stores as supporting distribution centers to offer quicker Buy-Online-Pickup-In-Store (BOPS) and Ship-From-Store (SFS) services. They resort to in-store picking to serve online orders using existing assets. However, in-store picking operations require picker carts traveling through store aisles, competing for store space, and possibly harming the offline customer experience. To learn picking policies that acknowledge interactions between pickers and offline customers, we formalize a new problem called Dynamic In-store Picker Routing Problem (diPRP). This problem considers a picker that tries to pick online orders (seeking) while minimizing customer encounters (hiding) – preserving the offline customer experience. We model the problem as a Markov Decision Process (MDP) and solve it using a hybrid solution approach comprising mathematical programming and reinforcement learning components. Computational experiments on synthetic instances suggest that the algorithm converges to efficient policies. We apply our solution approach in the context of a large European retailer to assess the proposed policies regarding the number of orders picked and customers encountered. The learned policies are also tested in six different retail settings, demonstrating the flexibility of the proposed approach. Our work suggests that retailers should be able to scale the in-store picking of online orders without jeopardizing the experience of offline customers. The policies learned using the proposed solution approach reduced the number of customer encounters by up to 50%, compared to policies solely focused on picking orders. Thus, to pursue omnichannel strategies that adequately trade-off operational efficiency and customer experience, retailers cannot rely on actual simplistic picking strategies, such as choosing the shortest possible route.

Instruments for Retail Sustainability

ИЗВЕСТИЯ НА СЪЮЗА НА УЧЕНИТЕ – ВАРНА СЕРИЯ ИКОНОМИЧЕСКИ НАУКИ, том 12 №1 2023 77 Instruments for Retail Sustainability Assoc. Prof. Dr. Michal Stojanov University of Economics – Varna, Varna, Bulgaria michal.stojanov@ue-varna.bg Abstract Human existence faces catastrophic natural and climatic threats and environmental factors that have reached a critical level. Today, with the greatest urgency, measures are put on the agenda and taken for implementation with a view to achieving a slowing rate of development of unfavorable and negative changes in the living environment. This requires every individual, business entity and government to change their traditional behavior and way of being with a view to reformation in the present, but with much greater and radical significance for the near future. The work systematizes a variety of tools, broad-spectrum policies and organizational-technological transformations applied in commerce, with a view to achieving sustainable development. The brief overview of leading European retailers confirms the commitment of modern retail business to make a contribution to achieving change in all 17 UN Sustainable Development Goals.

The periodic review model with independent age‐dependent lifetimes

A retailer places orders periodically for items that are shipped by a wholesaler. Items that are not sold perish randomly and independently of one another, with the perish probability depending on the age class. We consider a first‐in‐first‐out policy for depleting items. We model this problem as a Markov decision process with stochastic demand, unit holding, outdating and ordering costs, plus unit penalty costs for lost sales. We prove convexity for the penultimate period and show convexity may not hold any earlier. A dynamic program can be solved optimally for small instances. We introduce both a one‐stage‐lookahead heuristic and a heuristic which is a combination of two existing standard approaches, the newsvendor and periodic review models. For simulated data, we compare these heuristics to the optimal solution for small problem instances and to further lookahead policies for larger problem instances. We show that the two new heuristics achieve results close to optimal. Our numerical study, which includes real data from a large European retail chain, highlights that products perishing independently from each other strongly affect model behavior compared to existing approaches from the literature.

Embodied vs. Operational Energy and Carbon in Retail Building Shells: A Case Study in Portugal

(1) Background: The embodied energy of building materials is a significant contributor to climate change, in tandem with the energy use intensity (EUI). Yet, studies on the material impacts of European retail buildings, namely with relation to EUI, are missing. Hence, this study set out to: (i) evaluate the embodied energy and carbon emissions for a European retail building; (ii) quantify the material flow in terms of mass; (iii) compare the embodied aspects to the operational EUI and carbon use intensity (CUI); (iv) assess building materials with higher impacts; and (v) investigate strategies to mitigate materials’ impacts. (2) Methods: A Portuguese retail building was selected as a case study. A simplified LCA method was followed (cradle-to-gate), analysing the shell building materials in terms of primary energy demand and global warming potential. (3) Results: the embodied energy represented 32% of total lifecycle energy while the embodied carbon represented 94%. EUI was 1×kWh/m2/y while CUI was 21 kg CO2eq/m2/y. The embodied energy was 4248 kWh/m2, and the embodied carbon was 1689 kg CO2eq/m2. Cement mortar, steel, concrete, and extruded polystyrene were the most intensive materials. (4) Conclusions: The embodied impacts of the analysed store could decrease by choosing stone wool sandwich panels for the facades instead of extruded polystyrene panels and roof systems with metal sheet coverings instead of bitumen materials.

COVID-19 and sustainability in textile, apparel and fashion use: An assessment of trends

Apart from the many social and health problems it has caused, the COVID-19 pandemic has had a severe impact on most sectors of the economy worldwide. One of the areas where such impact is noticeable is the textile, apparel, and fashion (TAF) industry. The lockdowns and limited access to retailer outlets resulted in a considerable drop in consumption, creating problems related to the excess of stock, the decrease of sales, and the disposal of non-used items. This paper outlines the implications of the COVID-19 on the TAF sectors and European retailers. It analyzes how the current supply chains exacerbated stock control problems, and it reports on the changes in consumption during the pandemic. The worldwide restrictive measures implemented to cope with the COVID-19 pandemic were responsible for significant profit losses. Also, the decrease in consumption, caused by several geographically wide lockdowns, prompted a subsequent reduction in orders and sales, resulting in a significant number of constraints. The implementation of more environmentally friendly processes, including sustainable circularity as a competitiveness source to keep the TAF sectors in the loop and reduce greenhouse gas emissions, may help address the problems associated with the COVID-19 pandemic in the sustainability context, as reported in this paper.

Which Curve Fits Best: Fitting ROC Curve Models to Empirical Credit-Scoring Data

In the practice of credit-risk management, the models for receiver operating characteristic (ROC) curves are helpful in describing the shape of an ROC curve, estimating the discriminatory power of a scorecard, and generating ROC curves without underlying data. The primary purpose of this study is to review the ROC curve models proposed in the literature, primarily in biostatistics, and to fit them to actual credit-scoring ROC data in order to determine which models could be used in credit-risk-management practice. We list several theoretical models for an ROC curve and describe them in the credit-scoring context. The model list includes the binormal, bigamma, bibeta, bilogistic, power, and bifractal curves. The models are then tested against empirical credit-scoring ROC data from publicly available presentations and papers, as well as from European retail lending institutions. Except for the power curve, all the presented models fit the data quite well. However, based on the results and other favourable properties, it is suggested that the binormal curve is the preferred choice for modelling credit-scoring ROC curves.

Diversifying Entry, Resource Relatedness, and Redeployability: Evidence from a Natural Experiment

The topic of related diversification is of fundamental interest to strategy research. However, the understanding of how the potential for resource redeployment might encourage related diversification is limited. This paper explores the impact of the 2006 German real estate transfer tax (RETT) reform, which led to higher RETT rates but retained the exemption from RETT for corporate restructurings. We propose that firms might have reacted strategically to the threat of higher transfer taxes by combining closely related businesses into a portfolio, providing an efficient substitute market for reallocating property assets in the event of business-specific shocks. Consistent with a dynamic perspective on relatedness, difference-in-differences analyses of the European retail market show that the probability of entry into closely related businesses increased significantly for firms that were affected by the reform, relative to control firms. This finding contributes to the literature that links firm boundary choices to inter-temporal economies of scope and offers new insights into the real effects of transfer tax policies.

Reducing fresh fish waste while ensuring availability: Demand forecast using censored data and machine learning

Food waste reduction represents a potential opportunity to enhance environmental sustainability. This is especially important in fresh products such as fresh seafood, where waste levels are substantially higher than those of other food products. In this particular case, reducing waste is also vital to meet demand while conserving fisheries. This paper aims to promote more sustainable supply chains by proposing daily fresh fish demand forecasting models that can be used by grocery retailers to align supply and demand, and hence prevent the production of food waste. To accomplish this goal, we explored the potential of different machine learning models, namely Long Short-Term Memory networks, Feedforward neural networks, Support Vector Regression, and Random Forests, as well as a Holt-Winters statistical model. Demand censorship was considered to capture real demand. To validate the proposed methodology, we estimated the demand for fresh fish in a representative store of a large European retailing company used as a case study. The results revealed that the machine learning models provided accurate forecasts in comparison to the baseline models and the statistical model, with the Long Short-Term Memory networks model yielding, in general, the best results in terms of root mean squared error (27.82), mean absolute error (20.63) and mean positive error (17.86). Thus, the implementation of these types of models can thus have a positive impact on the sustainability of fresh fish species and customer satisfaction.

To collaborate and innovate for sustainability: Food retailers and their external partners

Firms collaborate with various organisations to address social and environmental issues. The existing literature has discussed such partnerships’ success factors and the opportunities they present, but few studies have provided an overview of the use of partnerships in the context of firms’ sustainability initiatives. This study investigated such sustainability partnerships, focusing on partnership mechanisms and choices of partners over time. Data were collected from 12 European retailers in the agri-food sector from 2014 through 2018 and analysed using content analysis methods. The analysis showed that during this period, the frequency of partnerships supporting philanthropic endeavours declined. Retailers simultaneously increased their use of partnerships to engage in sustainability-oriented innovation. They increasingly partnered with sustainability ventures while decreasing their partnerships with non-governmental organisations (NGOs). These changes in mechanism and partner choice may reflect a shift in retailers’ objectives from mainly engaging in legitimacy-oriented partnerships to exploring more participation in competence-oriented partnerships.

Evaluating human behaviour in response to AI recommendations for judgemental forecasting

Various advanced systems deploy artificial intelligence (AI) and machine learning (ML) to improve demand forecasting. Supply chain planners need to become familiar with these systems and trust them, considering real-world complexities and challenges the systems are exposed to. However, planners have the opportunity to intervene based on their experience or information that the systems may not capture. In this context, we study planners’ adjustments to AI-generated demand forecasts. We collect a large amount of data from a leading AI provider and a large European retailer. Our dataset contains 30 million forecasts at the SKU-store-day level for 2019, plus variables related to products, weather, and holidays. In our two-phase analysis, we aim to understand the adjustments made by planners and the quality of these adjustments. Within each phase, we first identify the drivers of adjustments and their quality using random forest, a well-known ML algorithm. Next, we investigate the collective effects of the different drivers on the occurrence and the quality of the adjustments using a decision tree approach. We find that product characteristics such as price, freshness, and discounts are important factors when making adjustments. Large positive adjustments occur more frequently but are often inaccurate, while large negative adjustments are generally more accurate but fewer in number. Thus, planners do not contribute to accuracy on average. Our findings provide insights for the better use of human knowledge in judgmental forecasting.

Analysis of the Food Loss and Waste Valorisation of Animal By-Products from the Retail Sector

The meat industry generates a large amount of animal by-products not only derived from the slaughter process but also due to the losses and waste of meat products along the supply chain, contributing to the world’s food loss and waste problem. Yearly, 1.7 Mt of meat in the European retail sector and 20% of meat for consumption is wasted in this sector of the supply chain. Therefore, the aim of this paper was to find and evaluate alternatives for the valorisation of agri-food residues, more specifically the meat waste from the food retail sector, through a technological perspective. Thus, we delve into the industrial processes already implemented and the emerging procedures that use muscle, bones and fats by-products from poultry, cattle and pork as the main raw materials in order to identify and characterise them. The results indicate that in addition to the current destinations—landfill, incineration and the rendering process—these animal by-products can be incorporated in the production of biodiesel, food formulations, pharmaceuticals, fertilisers and biogas through an industrial symbiosis approach. Consequently, the several valorisation processes and procedures identified not only suggest an increase in concern about the impacts of the disposal of these materials, but also highlight the potential associated with the use of animal by-products as raw material to obtain added-value products.

Mapping Product Returns Processes in Multichannel Retailing: Challenges and Opportunities

An increasing percentage of products in multichannel retail are being returned, yet many retailers and manufacturers are not aware of the importance and scale of this issue. Similarly, the literature on online returns is limited. Returns processes can be very complicated, contain many manual steps that have several variations, unclear decision-making rules and, at the handling stage, often involve low-wage third-party employees guided by patchy IT systems. This article maps the complexity of product returns processes, highlights challenges and identifies opportunities for improvement, thereby contributing to a deeper understanding of the emerging field of product returns research. It also concludes that it is essential for returns to be made a strategic priority at the senior management level, implementing a Lean approach to returns systems. The research was based on 4 case studies, 17 structured interviews and 3 retail community workshops, all with British and other Western European retailers. Through triangulation of individual data, a generic process map for retail returns was created and implications for sustainability, loss prevention and profit optimisation are examined.

Retail Practitioners’ Views vs. Ideal Theoretical Positions Concerning Ethical Business Practices with Garment Suppliers

The paper analyzes managers’ stance toward the ethical responsibility of those who work for multinational garment retailers. Most are charged with the social compliance policies affecting relationships with subcontractors. This study is based on interviews conducted with major European and American retailers. Our research question is: what is the normative stance of our respondents? We find that they reject the ideological way in which the normative debate on sweatshops has been conducted by business ethicists during the last decades. These executives’ implicit conception and scope of their moral responsibility is much more in line with Iris Young’s (2006) conception of ‘political responsibility’. This managerial ethical position has not been adequately captured by earlier writings on this topic. In general, the managerial ethical framing of issues like child labor, minimally decent labor conditions, a living wage, etc. is at odds with how these issues are usually treated in the philosophical debates around sweatshops. Examining both visions allows us to better grasp the pragmatic normative stance of business practitioners as well as the dynamics of social compliance policies. In the conclusion, we draw both management lessons and research implications for more ethical interactions with suppliers.

ГЛОБАЛІЗАЦІЙНІ ТРЕНДИ РОЗВИТКУ ЛІДЕРІВ СВІТОВОЇ РОЗДРІБНОЇ ТОРГІВЛІ

The state of development of world retail trade through the prism of the TOP 250 retailers functioning for 2013–2021 is considered in the article. Emphasis is placed on the strategic orientation of trading transnational companies on the business activities expansion on a global scale. The scope and nature of the internationalization of the largest trade networks activities is shown. The reasons for the manifestation of a different level of expansion by these structures are identified. It was found that the world’s leading retail trade networks have shown a slight increase in the values of their development indicators. The dynamics of the share of Top 250 trade companies by retail revenue from foreign operations is analyzed. It is established that the value of this indicator during 2013–2021 fluctuated slightly, but did not exceed 25% until 2020. Thus, the main source of income of Top 250 trade companies remained trade activities in national markets. The dynamics of the share of Top 250 trade companies by average number of foreign countries in 2013–2019 is analyzed. The analysis of the features of expansion policy manifestation by trade networks depending on the region of their origin, have been conducted. Special attention has paid to determining the place of European retailers in the Top 250 in the framework of the model of retail development. This model assumes the largest internationalization and active presence of trade networks in the markets of foreign countries. The structure of Top 250 companies by product sector is considered as well. The dynamics of retail revenue from foreign operations of Top 250 companies depending on their product range is analyzed. The nature of the largest trade networks presence in different segments of the consumer market during 2013–2019 is studied.