Search results

The purpose of this paper is to determine whether there is a difference in the development of shopping lists and use of advertisements as pre-store food-buying practices in terms of planned shopping by South African consumers who dwell in different socio-economic status (SES) areas. The paper also considers the influence of shopper and socio-demographic characteristics on pre-store food-buying practices in a developing country.

A self-administered questionnaire was used to survey 1 200 consumers in retail stores in low, middle and high SES areas in South Africa. A generalised linear model was employed for the statistical analysis of pre-store food-buying practices within the SES area groups in a developing country.

South African consumers that reside in high SES area displayed the largest of shopping list development, while consumers who dwell in low SES areas showed the highest incidence of advertisement usage. Several shopper and socio-demographic characteristics were also found to have an influence on pre-store food-buying practices in different SES areas in South Africa.

A qualitative approach would offer a deeper understanding of consumers’ pre-store food shopping predispositions as opposed to the quantitative approach, which was adopted for this study. A longitudinal design would also provide a more extensive representation of pre-store food shopping practices over a longer time frame than cross-sectional research. The survey was conducted on Saturdays, whereas consumers who shop during the week may have different shopping and socio-demographic characteristics.

Astute food brands, marketers and grocery stores could use the findings of this study to assist with their marketing efforts that they direct at consumers in different SES areas in South Africa and other developing countries.

The findings of this study may assist consumers in developing countries, especially those who reside in low SES areas, with food-buying strategies to reduce food costs, make wiser purchase decisions and reduce shopping.

No study (to the best of the researchers’ knowledge) has considered shopping list development and use of advertisements’ pre-store food-buying practices in different SES areas in a developing country. Furthermore, there is a dearth of research analysing shopper and socio-demographic characteristics in relation to pre-store food-buying practices among different SES areas in developing and developed countries.

Twenty-first century online retailing has reshaped the retail landscape. Grocery shopping is emerging as the next fastest growing category in online retailing in the UK, having implications for the channels we use to purchase goods. Using Sainsbury’s data, the authors create a bespoke set of grocery click&collect catchments. The resultant catchments allow an investigation of performance within the emerging channel of grocery click&collect. The paper aims to discuss these issues.

The spatial interaction method of “Huff gravity modeling” is applied in a semi-automated approach, used to calculate grocery click&collect catchments for 95 Sainsbury’s stores in England. The catchments allow investigation of the spatial variation and particularly rural-urban differences. Store and catchment characteristics are extracted and explored using ordinary least squares regression applied to investigate “demand per day” (a confidentiality transformed revenue value) as a function of competition, performance and geodemographic factors.

The findings show that rural stores exhibit a larger catchment extent for grocery click&collect when compared with urban stores. Linear regression finds store characteristics as having the greatest impact on demand per day, adhering to wider retail competition literature. Conclusions display a need for further investigation (e.g. quantifying loyalty).

New insights are contributed at a national level for grocery click&collect, as well as e-commerce, multichannel shopping and retail geography. Areas for further investigation are identified, particularly quantitatively capturing brand loyalty. The research has commercial impact as the catchments are being applied by Sainsbury’s to decide the next 100 stores and plan for the next five years of their grocery click&collect offering.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

The purpose of this paper is to achieve intelligent superstore site selection. Yonghui Superstores partnered with Cardinal Operations to incorporate a tremendous amount of site-related information (e.g. points of interest, population density and features, distribution of competitors, transportation, commercial ecosystem, existing own-store network) into its store site optimization.

This paper showcases the integration of regression, optimization and machine learning approaches in site selection, which has proven practical and effective.

The result was the development of the “Yonghui Intelligent Site Selection System” that includes three modules: business district scoring, intelligent site engine and precision sales forecasting. The application of this system helps to significantly reduce the labor force required to visit and investigate all potential sites, circumvent the pitfalls associated with possibly biased experience or intuition-based decision making and achieve the same population coverage as competitors while needing only half the number of stores as its competitors.

To our knowledge, this project is among the first to integrate regression, optimization and machine learning approaches in site selection. There is innovation in optimization techniques.

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 paper is to analyze the connections between the capabilities of suppliers, buyer operations and the innovation performance of buyers in service-based supply chains. In particular, the authors use a construct of supplier capabilities comprising the capabilities needed to produce an online store and divided into capabilities related to the product, capabilities related to service delivery and capabilities related to the buyer-supplier relationship.

Data were collected with cross-sectional, random sampling from Finnish companies that have an active online store. A survey was used to collect data on managerial assessments of capabilities of a supplier, the operations of buyers and the innovation performance of buyers. Multiple regressions were used to test the hypotheses.

The results reveal that capabilities related to the buyer-supplier relationship are positively connected with the innovation performance of the buyer, but those related to the product and service delivery do not significantly influence the innovation performance of the buyer. The results show that the moderating influence of buyer operations on the relationship between capabilities related to the product and the innovation performance of the buyer is negative. The moderating influence of buyer operations on the relationship between capabilities related to service delivery and the innovation performance of the buyer is positive.

Forming tight relationships with online store suppliers appears to be a successful way to attain innovation performance for online store operators. Online store operators should not expect supplier capabilities related to online store functionality and characteristics of online store delivery alone to improve their innovation performance.

Few studies use an e-business operations model to comprehend the role played by supplier capabilities in buyer innovation performance in service-based supply chains. Building on a resource-based view with inter-organizational management and e-business literature streams, the authors focus on three supplier capabilities and buyer operations to investigate their effects in terms of enhancing innovation performance.

This study aims to detect the dimensions of the in-store customer shopping experience from the sports retailer perspective and to investigate how the role of sports equipment stores is changing.

This exploratory study performs semi-structured interviews with retail managers of sports equipment stores.

This research reveals the importance of the dimensions of immersive design, sensorial ambient elements, social relationships, trialability and real experience sharing in designing a memorable in-store shopping experience in sports stores, and it highlights that the store's role in the sports context is transitioning from sales space to an interactive, immersive, engaging and convivial place. It proposes a model to design the in-store customer shopping experience effectively.

Sports equipment managers can make their physical stores as experiential as possible by investing in expert, passionate personnel and technology in order to create a real in-store experience of the product and the sports practice.

While sports equipment retailers acknowledge the importance of providing customers with a memorable shopping experience by creating an evocative environment and placing multiple touchpoints in stores, management scholars have paid limited attention to sports stores. This study explores the ways in which sports retail managers can design their stores effectively in experiential terms.

The purpose of this paper is to present a review of the implications building information modelling (BIM) is having on the building energy modelling (BEM) and design of buildings. It addresses the issues surrounding exchange of information throughout the design process, and where BIM may be useful in contributing to effective design progression and information availability.

Through review of current design procedures and examination of the concurrency between architectural and thermophysical design modelling, a procedure for information generation relevant to design stakeholders is created, and applied to a high-performance building project currently under development.

The extents of information key to the successful design of a buildings energy performance in relation to its architectural objectives are given, with indication of the level of development required at each stage of the design process.

BIM offers an extensible medium for parametric information storage, and its implementation in design development offers the capability to include BEM parameter-integrated construction information. The extent of information required for accurate BEM at stages of a building’s design is key to understanding how best to record performance information in a BIM environment.

This paper contributes to the discussion around the integration of concurrent design procedures and a common data environment. It presents a framework for the creation and dissemination of information during design, exemplifies this on a real building project and evaluates the barriers experienced in successful implementation.