Multiple Stores Research Articles

Implementation process for comprehensive medication review in the community pharmacy setting

ObjectivesTo (1) describe the implementation process for comprehensive medication reviews (CMRs) among community pharmacies (e.g., processes for prioritizing patients, staffing, and information collection) and (2) examine factors associated with community pharmacies’ CMR information collection process. MethodsA survey was administered to the pharmacist responsible for implementation of CMRs (i.e., the lead pharmacist) in the community pharmacy (n = 87). The survey included questions about pharmacy characteristics, satisfaction with the NC community pharmacy enhanced services network (NC-CPESN) program, and implementation of CMRs. Frequencies and means were calculated to describe the sample characteristics and pharmacies’ CMR implementation process. A multiple linear regression was conducted to examine which characteristics were associated with the CMR information collection process. ResultsThe majority of pharmacies in the sample were either independently owned single stores (46.5%) or multiple stores under the same independent ownership (41.6%). Most pharmacies used pharmacists (97.7%) or pharmacy technicians (65.5%) for patient outreach for CMRs. A small percentage of pharmacies used administrative staff to conduct patient outreach for CMRs (9.2%). Information for prescription medications (89.5%), indication (80%), and medication adherence (81.1%) was routinely collected. Information such as date of last dose for prescription medications (48.4%) and lifestyle factors, such as physical activity (21.1%), diet (29.5%), and alcohol (31.6%), was collected less routinely. Having a clinical pharmacist (P = 0.025) and pharmacist overlap hours (P = 0.009) significantly improved the CMR information collection process. ConclusionAlthough CMRs are important interventions for improving patient outcomes, more guidance is needed on how to effectively implement them. This would allow the process to be efficient and assure implementation with fidelity across all community pharmacies. In addition, staffing appears to influence the quality of CMR information collection. Future research is warranted on CMR implementation to develop efficient staffing models and standardize the process of information collection.

On store languages and applications

The store language of a machine of some arbitrary type is the set of all store configurations (state plus store contents but not input) that can appear in an accepting computation. New algorithms and characterizations of store languages are obtained, such as the result that any nondeterministic pushdown automaton augmented with reversal-bounded counters, where the pushdown can “flip” its contents a bounded number of times, can be accepted by a machine with only reversal-bounded counters. Connections are made between store languages and several model checking and reachability problems, such as accepting the set of all predecessor and successor configurations of a machine from a given (regular) set of configurations. For a variety of different machine models often containing multiple parallel data stores, these sets can be accepted with a machine model that is simpler than the original model itself. Store languages are key to showing these properties.

Bayesian Method for Causal Inference in Spatially-Correlated Multivariate Time Series

Measuring the causal impact of an advertising campaign on sales is an essential task for advertising companies. Challenges arise when companies run advertising campaigns in multiple stores which are spatially correlated, and when the sales data have a low signal-to-noise ratio which makes the advertising effects hard to detect. This paper proposes a solution to address both of these challenges. A novel Bayesian method is proposed to detect weaker impacts and a multivariate structural time series model is used to capture the spatial correlation between stores through placing a G-Wishart prior on the precision matrix. The new method is to compare two posterior distributions of a latent variable—one obtained by using the observed data from the test stores and the other one obtained by using the data from their counterfactual potential outcomes. The counterfactual potential outcomes are estimated from the data of synthetic controls, each of which is a linear combination of sales figures at many control stores over the causal period. Control stores are selected using a revised Expectation-Maximization variable selection (EMVS) method. A two-stage algorithm is proposed to estimate the parameters of the model. To prevent the prediction intervals from being explosive, a stationarity constraint is imposed on the local linear trend of the model through a recently proposed prior. The benefit of using this prior is discussed in this paper. A detailed simulation study shows the effectiveness of using our proposed method to detect weaker causal impact. The new method is applied to measure the causal effect of an advertising campaign for a consumer product sold at stores of a large national retail chain.

Is online multiple-stores cooperative promotion better than single-store promotion? Misprediction from evaluation mode

Inspired by the evaluation mode theory, we show online vendors mispredict consumers’ responses to different types of sales displays. While vendors predict that consumers evaluate a featured product more positively in a cooperative sales promotion (CSP; i.e., multiple stores promoting synchronously) than in an independent sales promotion (ISP; i.e., a single store promoting independently), consumers actually do the opposite. The reason is that vendors compare CSP with ISP and are able to evaluate depending on perceived acquisition utility; consumers, however, see either CSP or ISP, resulting in difficulty in accessing acquisition utility. Thus, they evaluate according to perceived transaction utility.

Is Online Multiple-Stores Cooperative Promotion Better than Single-Store Promotion? Misprediction from Evaluation Mode

Inspired by the evaluation mode theory, we show online vendors mispredict consumers' responses to different types of sales displays. While vendors predict that consumers evaluate a featured product more positively in a cooperative sales promotion (CSP; i.e., multiple stores promoting synchronously) than in an independent sales promotion (ISP; i.e., a single store promoting independently), consumers actually do the opposite. The reason is that vendors compare CSP with ISP and are able to evaluate depending on perceived acquisition utility; consumers, however, see either CSP or ISP, resulting in difficulty in accessing acquisition utility. Thus, they evaluate according to perceived transaction utility.

The Value of Same-Day Delivery

The growth of the online economy can either reinforce or attenuate disparities in access to retail depending on the nature of its interaction with consumers’ offline vicinity. This paper measures the welfare value of new online grocery services and identifies the channels through which consumers benefit from this innovation. I construct a new dataset with the roll-out of two grocery delivery platforms to show how their different delivery logistics affect consumers. I combine this geographic entry information with scanner data to estimate a Revealed Preference model where consumers choose over bundles of products and retailers. I find the new services to be worth on average $120/year to users. If delivery logistics rely on partnerships with local stores, households that live close to multiple retail stores are the most likely to gain access to the new technology. This complementarity between the delivery service and the consumer’s geographic location benefits high income zip codes 34% more than low income zip codes due to differences in the supply of offline retail. On the other hand, distance to brick-and-mortar retail makes delivery a more valuable substitute to the offline economy. The value creation through this channel is 26% larger in low income zip codes compared to high income ones.

Functional and environmental impact analysis of urban deliveries in a Brazilian historical city

This study aims to characterize the transportation of urban goods from multiple retail stores in the Brazilian municipality São João Del Rei, in the state of Minas Gerais, as well as measure the environmental impact in terms of CO2 emissions. The study takes place in the downtown part of the city, which depends on a wide range of companies to provide employment, products and services for a large part of the city’s population, along with neighboring cities. As a historical heritage city, the traditional city streets reflect planning from a long time ago, during a time in which modern transportation vehicles and services were practically nonexistent. These factors make commerce in the downtown region a particular challenge for the urban organism. To better understand this scenario and indicate measurements to improve the functioning of the urban transportation network, 152 companies responded to interview questions about the main implicit variables in their goods receiving processes, along with information regarding cargo and vehicle types, trips and infrastructure. Any measure taken to mitigate these problems must obligatorily consider the historic nature of the city and establish coherence between the conflicting objectives of the diverse actors which make up the urban environment. The results show the need for creation of new policies for urban logistics, including more areas reserved for loading and unloading of cargo, along with greater monitoring these areas from authorities to guarantee that the law is upheld. Emission reductions are achieved using freight demand management such as off-hour deliveries and investing in technology to reduce emissions from delivery trucks.

Do the different store formats of the same brand matter to Chinese customers? An International study on a Japanese fashion brand

ABSTRACTMany retailers have recently been building a greater variety of store formats and attempting to provide a superior shopping experience through their store environment in order to increase the possibility of customer revisitation and customer loyalty. However, less research pays attention to the issue of how, and to what extent, the different store formats have on impacting customer satisfaction and loyalty building. In order to improve the understanding of the satisfaction–loyalty link in the context of retail internationalization, we survey a Japanese fashion company – Nice Claup – that segmented the Chinese market by operating multiple retail stores and each retail store plays a discrete role of cultivating customer loyalty. Through 388-customer survey data, the results suggest that while attitudinal loyalty positively and directly influences behavioral loyalty, satisfaction indirectly drives behavioral loyalty through the mediating effects of attitudinal loyalty. The implication is that an application of implementing retail internationalization with adopting multiple store formats on different types of customers and customer behavioral loyalty can be transferred by offering multi-brands store more effectively than the single-brand store in the Chinese fashion market.

Inventory optimization model considering consumer shift and inventory transshipment in dual-channel supply chains

In this paper we consider a dual-channel supply chain which consists of an online store and multiple independent retail stores. In this system, customer shift induces inventory competition while transshipment brings inventory cooperation, both of which inuences inventory optimization and control. Therefore we respectively construct inventory optimization models under the two situations: customer shift and inventory transshipment. Specifically, unilateral customer shift and inventory transshipment are considered, and a one-for-one replenishment strategy is applied. We first solve the equilibrium state probability of on-hand inventory through Markov chain theory, then optimize performance measure (i.e., the total costs) to obtain the optimal basic inventory level. Finally, we analyze the impact of customer shift rate and inventory transshipment rate on the inventory strategies through numerical simulation, and further compare the differences in inventory decisions between the above two situations, which prove that inventory cooperation brought by inventory transshipment is not necessarily better than inventory competition brought by customer shift. In addition, we discuss several insights that are evident from the parametric analysis of the model.

Efficiency assessment of Indian electronics retail stores using DEA

Retail plays an important role in creating a link between upstream stages of a supply chain and the end customers. Supply chains can create higher customer value and competitive advantage if retailers are capable of extending their capabilities and performance. It is imperative for retail businesses to monitor their performance based on appropriate performance measures and devise strategies for continuous improvements. This study presents the methodology for selection of performance assessment measures integrating fuzzy Delphi and data envelopment analysis (DEA) selective measure methods; and then compute the relative efficiency of multiple stores of an Indian Electronics retail chain following the DEA method. The overall performance of a retail chain rest on the individual store's performance and hence it is all the more important for the inefficient stores to benchmark the performance of the efficient stores. Subsequent to efficiency measurement, super efficiency scores are computed to rank the efficient stores and input/output slack are determined for inefficient stores to help practitioners in planning strategies for benchmarking and performance enhancement.

Efficiency assessment of Indian electronics retail stores using DEA

Retail plays an important role in creating a link between upstream stages of a supply chain and the end customers. Supply chains can create higher customer value and competitive advantage if retailers are capable of extending their capabilities and performance. It is imperative for retail businesses to monitor their performance based on appropriate performance measures and devise strategies for continuous improvements. This study presents the methodology for selection of performance assessment measures integrating fuzzy Delphi and data envelopment analysis (DEA) selective measure methods; and then compute the relative efficiency of multiple stores of an Indian Electronics retail chain following the DEA method. The overall performance of a retail chain rest on the individual store's performance and hence it is all the more important for the inefficient stores to benchmark the performance of the efficient stores. Subsequent to efficiency measurement, super efficiency scores are computed to rank the efficient stores and input/output slack are determined for inefficient stores to help practitioners in planning strategies for benchmarking and performance enhancement.

Analyzing Authentication Patterns for Cloud Services

Cloud services are very popular among enterprises; most businesses use multiple cloud services. At the same time, some enterprises acquire, merge, and partner with other companies. It is at that point where one party will need to access the other party?s resources in the cloud as well as its private cloud services. Due to these complex connections, cloud services must deal with different authentication protocols, multiple heterogeneous user stores, and legacy identity systems. As a result, implementing authentication in the cloud has become riskier and more complex.

Visual Comparison of Customer Stickiness in Retail Stores

Understanding market trends and forming competitive promotion strategies has always been a major task of retail store managers. One big challenge is the lack of effiective tools for in-depth customer behavior analysis. In this paper, we apply visual analytics techniques to address the challenge, which is built up on the emerging and mobile location big data. We present a system that focuses on the analysis of customer stickiness which represents customers' affinity to retail stores. The system integrates mobile data pre-processing, customer stickiness analysis, multi-view visualization, and a set of interactions. The visual analytics techniques are mainly designed for two types of user tasks: 1) understanding the spatio-temporal distribution of customer traces related to retail stores; 2) evaluating the performance and trend of multiple retail stores through visual comparison. We have demonstrated the effiectiveness of the system through two case studies including advertisement placement and business branch reconfiguration.

Fruit and Vegetable Intake of US Hispanics by Food Store Type: Findings from NHANES.

This study examined fruit and vegetable intake by food store type shopped among US Hispanics. Using National Health and Nutrition Examination Survey 2011-2012 data, T test and chi-square tests examined differences between Hispanic consumers by food store type. Negative binomial regression analyses estimated associations between fruit and vegetable intake and food store type. Hispanics who only purchased fruits and vegetables from convenience stores were younger and more likely US born. They reported lower intakes of fruit and vegetables than individuals who purchased these foods from supermarket/grocery stores. Those who primarily purchased fruits and vegetables from supermarkets/grocery stores consumed 0.92 (p < .001) greater fruit cup equivalents and 0.26 (p = .001) greater vegetable cup equivalents than those who only purchased from convenience stores. Research on the influence of shopping in multiple food store types is needed to develop targeted in-store intervention strategies to encourage healthier food purchases. Results provide support for policy-level research such as minimum stocking requirements for healthy foods in convenience stores.

Associations between proposed local government liquor store size classifications and alcohol consumption in young adults

The prevalence of warehouse-style liquor stores has prompted alarm from local communities and public health advocates. To increase local government control over liquor stores, one proposed planning response is to distinguish between ‘small’ (i.e., ≤ 300 m2) and ‘large’ (i.e., > 300 m2) liquor stores. We mapped the size and location of liquor stores in Perth, Western Australia, and tested associations between liquor store exposure and alcohol consumption (grams ethanol/day) in young adults (n = 990). The count of liquor stores of any size within 1600 m and 1601–5000 m of home were significantly associated with increased alcohol intake, whereas larger stores (i.e., > 300 m2 and > 600 m2) were not associated with alcohol intake. Young adults’ alcohol consumption appears to be impacted by liquor store density and convenience, rather than outlet size. However, the presence of multiple stores close to home increases market competition, driving alcohol prices down, and plausibly results in alcohol prices similar to those at liquor superstores.

Complex Queries Optimization and Evaluation over Relational and NoSQL Data Stores in Cloud Environments

The production of huge amount of data and the emergence of cloud computing have introduced new requirements for data management. Many applications need to interact with several heterogeneous data stores depending on the type of data they have to manage: relational and NoSQL (i.e., document, graph, key-value, and column) data stores. Interacting with heterogeneous data models via different APIs and query languages imposes challenging tasks to the developers of multiple data stores applications. Indeed, the execution of complex queries over heterogeneous data models cannot, currently, be achieved in a declarative way as it is used to be with single data store application, and therefore requires extra implementation efforts. In this paper we propose a mediation based component to optimize and execute complex queries over multiple data stores in Cloud environments. This component is referred to as virtual data store (VDS). The key ingredients of our solution are (1) a simple global schema describing the different data sources and their relationships, (2) a cost model to evaluate the cost of the operations, (3) an inter data stores parallelism execution model, and (4) a dynamic programming based approach to generate optimal execution plan. Quantitative and qualitative experiments are conducted to validate our approach.

Relationship between pharmacy characteristics and pharmacy performance

To (1) describe the implementation process for comprehensive medication reviews (CMRs) among community pharmacies (e.g., processes for prioritizing patients, staffing, and information collection) and (2) examine factors associated with community pharmacies’ CMR information collection process.A survey was administered to the pharmacist responsible for implementation of CMRs (i.e., the lead pharmacist) in the community pharmacy (n = 87). The survey included questions about pharmacy characteristics, satisfaction with the NC community pharmacy enhanced services network (NC-CPESN) program, and implementation of CMRs. Frequencies and means were calculated to describe the sample characteristics and pharmacies’ CMR implementation process. A multiple linear regression was conducted to examine which characteristics were associated with the CMR information collection process.The majority of pharmacies in the sample were either independently owned single stores (46.5%) or multiple stores under the same independent ownership (41.6%). Most pharmacies used pharmacists (97.7%) or pharmacy technicians (65.5%) for patient outreach for CMRs. A small percentage of pharmacies used administrative staff to conduct patient outreach for CMRs (9.2%). Information for prescription medications (89.5%), indication (80%), and medication adherence (81.1%) was routinely collected. Information such as date of last dose for prescription medications (48.4%) and lifestyle factors, such as physical activity (21.1%), diet (29.5%), and alcohol (31.6%), was collected less routinely. Having a clinical pharmacist (P = 0.025) and pharmacist overlap hours (P = 0.009) significantly improved the CMR information collection process.Although CMRs are important interventions for improving patient outcomes, more guidance is needed on how to effectively implement them. This would allow the process to be efficient and assure implementation with fidelity across all community pharmacies. In addition, staffing appears to influence the quality of CMR information collection. Future research is warranted on CMR implementation to develop efficient staffing models and standardize the process of information collection.

Optimizing case-pack sizes in the bricks-and-mortar retail trade

Before reaching the store, products generally flow through the retail distribution system as larger bundles, the so-called case packs (CP). In several studies these case packs have been identified as having a significant impact on distribution logistics efficiency. In this paper we develop a quantitative model and solution approach determining optimal case-pack sizes for non-perishable products in grocery retailing. The model captures the relevant operative cost drivers along the internal supply chain of a large bricks-and-mortar retailer. It explicitly represents each day of the retailer’s business week, where the replenishment doctrine considered generalizes the well-known periodic review reorder point (r, s, nq) policy as a stationary cyclic version. Exact and approximate methods are developed to evaluate the costs of a model instance. In addition, an optimization procedure is outlined that uses either exact or approximate methods to identify optimal and near-optimal CP sizes for a single store as well as for a network of multiple stores to be operated with one common CP. Applied to real-world examples of a large European retail chain, the methods reveal average cost improvement potential of more than 20% by adjusting the CP sizes that are currently in use. The approach presented is thus shown to be a valuable addition to any integrative retail supply chain planning system. Its results are directly applicable to retail practice.

Impact of storage competition on energy markets

We study how storage, operating as a price maker within a market environment, may be optimally operated over an extended period of time. The optimality criterion may be the maximisation of the profit of the storage itself, where this profit results from the exploitation of the differences in market clearing prices at different times. Alternatively it may be the minimisation of the cost of generation, or the maximisation of consumer surplus or social welfare. In all cases there is calculated for each successive time-step the cost function measuring the total impact of whatever action is taken by the storage. The succession of such cost functions provides the information for the storage to determine how to behave over time, forming the basis of the appropriate optimisation problem.We study particularly competition between multiple stores, where the objective of each store is to maximise its own income given the activities of the remainder. We show that, at the Cournot Nash equilibrium, multiple stores which between them have market impact collectively erode their own abilities to make profits: essentially each store attempts to increase its own profit over time by overcompeting at the expense of the remainder. We quantify this for linear price functions.We give examples throughout based on electricity storage and Great Britain electricity spot-price market data.

Save or (over-)spend? The impact of hard-discounter shopping on consumers' grocery outlay

An increasing number of consumers have come to patronize a hard discounter (HD) to save on their grocery budget. Given the HDs' rock-bottom prices, a complete switch from the traditional supermarket (TS) to the HD format would, indeed, substantially reduce grocery spending. However, consumers typically visit the HD on top of a TS, leading to a more complex purchase allocation and decision process. In addition to limiting the potential savings to part of the basket, these multiple store shopping patterns may therefore result in depletion of self-control resources and to self-licensing, consumers using realized savings to justify additional indulgent purchases. In this study, we explain and empirically analyze the effect of HD patronage on consumer spending, taking the selected shopping pattern (single versus multiple stores, visited on separate versus combined shopping trips) into account. To this end, we use scanner panel data on households' actual weekly purchase behavior. We also examine household differences in these effects, and relate them to household characteristics.Our results show that shifting the entire basket to the HD entails substantial savings. Yet, for the majority of consumers, adding a HD to the store set does not reduce grocery outlay: visiting the HD and TS on separate shopping trips leads to a “status quo”, and visiting them on combined shopping trips even enhances weekly spending. While consumers pay less per unit bought at the HD, this is (more than) offset by the purchase of larger quantities across a broad range of product categories, and of more expensive items at the TS. Especially older consumers or larger households, and consumers who shop more frequently or are easily enticed by promotions, are bound to overspend.