Inequalities in retail choice: exploring consumer experiences in suburban neighbourhoods

Focuses on deprived neighbourhoods where instances of “food deserts” have been found and explores, through focus groups, consumer experiences of food store choices. Focusing on suburban neighbourhoods in Portsmouth, identifies significant differences in experiences of choice both between and within neighbourhoods. In some localities, the research also finds dissatisfaction with the (supposedly-coveted) “small local store”. Shows that choice is very different from provision, and conceptualises how consumers’ circumstances, situation and individual characteristics can significantly reduce a broad theoretical provision of food stores to a limited set of perceived real choices.

The effects of store atmosphere on shopping behaviour - A literature review.

This paper provides an insight into how the atmospherics of a retail environment influence shopping behaviour. Its objective is to support researchers and practitioners by summarizing the current state of knowledge and identifying gaps and avenues for future research. The scope covers studies in retail marketing and environmental psychology published during the last 35 years. It has been shown that environmental cues (music, scent etc.) have an effect on the emotional state of the consumer, which in turn causes behavioural changes, both positive (approach, buy more, stay longer etc.) and negative (not approach, buy less, leave earlier etc.). Most studies make reference to the PAD model, which proposes that the relevant emotions in this process can be measured along three dimensions Pleasure, Arousal and Dominance (Mehrabian, A. & Russell, J.A.,1974, An approach to environmental psychology, Cambridge, MA.: MIT Press). Since then, significant advances have been made to understand the effect of individual cues, their interaction, as well as the role of moderators, such as gender, age, or shopping motivation. However, there are a number of opportunities for further research. Too little is known about the moderating effects of Arousal and Dominance and how they interact with each other and with Pleasure dimension. Also a number of other moderators, such as gender and culture, should be integrated into the model.

What Makes Online Grocers Work? A Case Study Analysis of Factors Contributing to Online Grocery Store Profitability

This research examined the factors contributing to the performance of online grocers prior to, and following, the 2000 dot.com collapse. The primary goals were to assess the relationship between a company’s business model(s) and its performance in the online grocery channel and to determine if there were other company and/or market related factors that could account for company performance. To assess the primary goals, a case based theory building process was utilized. A three-way cross-case analysis comprising Peapod, GroceryWorks, and Tesco examined the common profit components, the structural category (e.g., pure-play, partnership, and hybrid) profit components, and the idiosyncratic profit components related to each specific company. Based on the analysis, it was determined that online grocery store business models could be represented at three distinct, but hierarchically, related levels. The first level was termed the core model and represented the basic profit structure that all online grocers needed in order to conduct operations. The next model level was termed the structural model and represented the profit structure associated with the specific business model configuration (i.e., pure-play, partnership, hybrid). The last model level was termed the augmented model and represented the company’s business model when idiosyncratic profit components were included. In relation to the five company related factors, scalability, rate of expansion, and the automation level were potential candidates for helping to explain online grocer performance. In addition, all the market structure related factors were deemed possible candidates for helping to explain online grocer performance. The study concluded by positing an alternative hypothesis concerning the performance of online grocers. Prior to this study, the prevailing wisdom was that the business models were the primary cause of online grocer performance. However, based on the core model analysis, it was hypothesized that the customer relationship activities (i.e., advertising, promotions, and loyalty program tie-ins) were the real drivers of online grocer performance.

Waste Not, Want Not: Managing Perishables in Small and Medium Retail Enterprises

Purpose of this paper:
Recent literature indicates that around one third of perishable products finish as waste (Mena et al., 2014): 60% of this waste can be classified as avoidable (EC, 2010) suggesting logistics and operational inefficiencies along the supply chain. In developed countries perishable products are predominantly wasted in wholesale and retail (Gustavsson et al., 2011) due to customer demand uncertainty the errors and delays in the supply chain (Fernie and Sparks, 2014). While research on logistics of large retail supply chains is well documented, research on retail small and medium enterprises’ (SMEs) capabilities to prevent and manage waste of perishable products is in its infancy (c.f. Ellegaard, 2008) and needs further exploration. In our study, we investigate the retail logistics practice of small food retailers, the factors that contribute to perishable products waste and the barriers and opportunities of SMEs in retail logistics to preserve product quality and participate in reverse logistics flows.

Design/methodology/approach:
As research on waste of perishable products for SMEs is scattered, we focus on identifying key variables that contribute to the creation of avoidable waste. Secondly we identify patterns of waste creation at the retail level and its possibilities for value added recovery. We use explorative case studies (Eisenhardt, 1989) and compare four SMEs and one large retailer that operate in a developed market. To get insights into specificities of SMEs that affect retail logistics practice, we select two types of food retailers: specialised (e.g. greengrocers and bakers) and general (e.g. convenience store that sells perishable products as a part of the assortment)

Findings:
Our preliminary findings indicate that there is a difference between large retailers and SME retailers in factors that contribute to the waste creation, as well as opportunities for value added recovery of products. While more factors appear to affect waste creation and management at large retailers, a small number of specific factors appears to affect SMEs. Similarly, large retailers utilise a range of practices to reduce risks of product perishability and short shelf life, manage demand, and manage reverse logistics practices. Retail SMEs on the other hand have limited options to address waste creation and value added recovery. However, our findings show that specialist SMEs could successfully minimize waste and even create possibilities for value added recovery of perishable products. Data indicates that business orientation of the SME, the buyersupplier relationship, and an extent of adoption of lean principles in retail coupled with SME resources, product specific regulations and support from local authorities for waste management or partnerships with other organizations determine extent of successful preservation of a product quality and value added recovery.

Value:
Our contribution to the SCM academic literature is threefold: first, we identify major factors that contribute to the generation waste of perishable products in retail environment; second, we identify possibilities for value added recovery for perishable products and third, we present opportunities and challenges for SME retailers to manage or participate in activities of value added recovery. Our findings contribute to theory by filling a gap in the literature that considers product quality preservation and value added recovery in the context of retail logistics and SMEs.

Research limitations/implications:
Our findings are limited to insights from five case studies of retail companies that operate within a developed market. To improve on generalisability, we intend to increase the number of cases and include data obtained from the suppliers and organizations involved in reverse logistics flows (e.g. local authorities, charities, etc.).

Practical implications:
With this paper, we contribute to the improvement of retail logistics and operations in SMEs which constitute over 99% of business activities in UK (Rhodes, 2015). Our findings will help retail managers and owners to better understand the possibilities for value added recovery, investigate a range of logistics and retail strategies suitable for the specificities of SME environment and, ultimately, improve their profitability and sustainability.

The Impact of Supervisory Monitoring On High-End Retail Sales Productivity

Based on a two-stage analysis of a panel of data on 12 outlets of a high-end retailer for 24 months, we investigate how the level of supervisory monitoring affects retail sales productivity. In the first stage, we use Data Envelopment Analysis (DEA) to compute the relative productivity of retail outlets in using their labor and capital resources to generate store sales. In the second stage, we regress the logarithm of DEA scores on contextual variables to obtain consistent estimators of the impact of contextual variables on productivity (Banker and Natarajan in Operation Research 56:48-58, 2008). Contrary to agency theoretic prediction that supervisory monitoring leads to an increase in retail sales productivity, our empirical results indicate that the higher the level of supervisory monitoring, the lower is the retail sales productivity for high-end retail outlets.

Using Intelligent Agents to Understand Management Practices and Retail Productivity

Intelligent agents offer a new and exciting way of understanding the world of work. In this paper we apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents could offer potential for fostering sustainable organizational capabilities in the future. The project is still at an early stage. So far we have conducted a case study in a UK department store to collect data and capture impressions about operations and actors within departments. Furthermore, based on our case study we have built and tested our first version of a retail branch simulator which we will present in this paper.

Understanding Retail Productivity by Simulating Management Practices

Intelligent agents offer a new and exciting way of understanding the world of work. In this paper we apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents could offer potential for fostering sustainable organizational capabilities in the future. Our research so far has led us to conduct case study work with a top ten UK retailer, collecting data in four departments in two stores. Based on our case study data we have built and tested a first version of a department store simulator. In this paper we will report on the current development of our simulator which includes new features concerning more realistic data on the pattern of footfall during the day and the week, a more differentiated view of customers, and the evolution of customers over time. This allows us to investigate more complex scenarios and to analyze the impact of various management practices.

A Multi-Agent Simulation of Retail Management Practices

We apply Agent-Based Modeling and Simulation (ABMS) to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents do offer potential for developing organizational capabilities in the future. Our multi-disciplinary research team has worked with a UK department store to collect data and capture perceptions about operations from actors within departments. Based on this case study work, we have built a simulator that we present in this paper. We then use the simulator to gather empirical evidence regarding two specific management practices: empowerment and employee development.

An agent-based simulation of in-store customer experiences

Agent-based modelling and simulation offers a new and exciting way of understanding the world of work. In this paper we describe the development of an agent-based simulation model, designed to help to understand the relationship between human resource management practices and retail productivity. We report on the current development of our simulation model which includes new features concerning the evolution of customers over time. To test some of these features we have conducted a series of experiments dealing with customer pool sizes, standard and noise reduction modes, and the spread of the word of mouth. Our multidisciplinary research team draws upon expertise from work psychologists and computer scientists. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents offer potential for fostering sustainable organisational capabilities in the future.

How to optimize the traditional retail market for FMCG sector?

Field lab: Entrepreneurial and innovative ventures

Simulating customer experience and word-of-mouth in retail: a case study

Agents offer a new and exciting way of understanding the world of work. In this paper we describe the development of agent-based simulation models, designed to help to understand the relationship between people management practices and retail performance. We report on the current development of our simulation models which includes new features concerning the evolution of customers over time. To test the features we have conducted a series of experiments dealing with customer pool sizes, standard and noise reduction modes, and the spread of customers’ word of mouth. To validate and evaluate our model, we introduce new performance measure specific to retail operations. We show that by varying different parameters in our model we can simulate a range of customer experiences leading to significant differences in performance measures. Ultimately, we are interested in better understanding the impact of changes in staff behavior due to changes in store management practices. Our multi-disciplinary research team draws upon expertise from work psychologists and computer scientists. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents offer potential for fostering sustainable organizational capabilities in the future.