Local Retail Stores Research Articles

The Power of Neuromarketing as a Fuel to Drive Purchases in Local Retail (Piura 2024")

Neuromarketing studies the neurological brain responses to various marketing stimuli, such as visual, sound, colour and emotional elements, in order to understand in depth the cognitive and affective processes associated with consumer decision-making. Given its relevance, the objective is to determine how the power of neuromarketing acts as a fuel to drive purchase in a local retail store - Piura 2024. Methodologically, a quantitative approach was used with a non-experimental, descriptive-correlational and transversal design. A total of 384 frequent customers, of legal age and with purchasing power, participated. The findings of this study are an irrefutable testimony to the transformative power of neuromarketing in this local setting (Piura). With a Spearman correlation coefficient of 0.823 (p < 0.01), a strong and statistically significant positive correlation between neuromarketing and purchase decision is revealed, demonstrating that this innovative discipline has the ability to profoundly influence consumer behaviour. These results are a call to action for companies in the sector to adopt neuromarketing strategies that allow them to connect with their customers in a more effective and emotional way, thus unleashing an unprecedented impact on their commercial success. Received: 4 August 2024 / Accepted: 29 October 2024 / Published: 05 November 2024

Comparison of real-time PCR and nested PCR based on the HlyA gene for the detection of Listeria monocytogenes. Application on cheese samples.

The aim of the present study was to compare the performance of a nested polymerase chain reaction (nPCR) and a real-time PCR based on the amplification of the HlyA gene from Listeria monocytogenes using a plasmid DNA standard. Nested PCR was developed with an internal amplification control (IAC). Both techniques were validated in soft cheese samples by comparing their results with the results of the microbiological reference method ISO 11290-1:2017. Cheese samples artificially contaminated with 3.5 to 3,500 UFC/25g were processed by ISO 11290-1:2017 and, at several times of culture, DNA samples were extracted. All cheeses contaminated with L. monocytogenes were positive for the microbiological method 96h post contamination and for nPCR and real-time PCR 48h post contamination. At this time, the HlyA gene was amplified in all contaminated samples. Both molecular techniques showed the same sensitivity, 30 copies/reaction or 3.5 UFC/25g, when plasmid DNA standard or artificially contaminated cheese samples were used. Finally, eighty soft cheese samples obtained from local retail stores and tested by three methods were negative, indicating a 100% concordance in results. The development of an nPCR with IAC reinforces the reliability of the negative results without increasing the costs of the reaction. Besides, nPCR showed less sensitivity to the presence of inhibitory substances in the reaction. The use of one of these molecular techniques could be easily coupled to the microbiological method, serving as a screening method in the food industry for hygiene monitoring and early identification of contaminated foods.

Bacterial profile of pork from production to retail based on high-throughput sequencing

Pork is a common vehicle for foodborne pathogens, including Salmonella spp. and Yersinia enterocolitica. Cross-contamination can occur at any stage of the pork production chain, from farm to market. In the present study, high-throughput sequencing was used to characterize bacterial profiles and track their changes along the whole supply chain. Tracked meat samples (pig on the farm, carcass in the slaughterhouse, unprocessed carcass and processed meat in the processing plant, and fresh pork at the local retail stores) and their associated environmental samples (e.g., water, floor, feed, feces, and workers' gloves) were collected from sequential stages (n = 96) and subjected to 16S rRNA metataxonomic analyses. At the farm, a total of 652 genera and 146 exclusive genera were identified in animal and environmental samples (pig, drain, floor, fan, and feces). Based on beta diversity analysis, it was demonstrated that the microbial composition of animal samples collected at the same processing step is similar to that of environmental samples (e.g., drain, fan, feces, feed, floor, gloves, knives, tables, and water). All animal and environmental samples from the slaughterhouse were dominated by Acinetobacter (55.37 %). At the processing plant, belly meat and neck meat samples were dominated by Psychrobacter (55.49 %). At the retail level, key bacterial players, which are potential problematic bacteria and important members with a high relative abundance in the samples, included Acinetobacter (8.13 %), Pseudomonas (6.27 %), and Staphylococcus (2.13 %). In addition, the number of confirmed genera varied by more than twice that identified in the processing plant. Source tracking was performed to identify bacterial contamination routes in pork processing. Animal samples, including the processing plant's carcass, the pig from the farm, and the unwashed carcass from the slaughterhouse (77.45 %), along with the processing plant's gloves (5.71 %), were the primary bacterial sources in the final product. The present study provides in-depth knowledge about the bacterial players and contamination points within the pork production chain. Effective control measures are needed to control pathogens and major pollutants at each stage of pork production to improve food safety.

Where you live matters: The impact of offline retail density on mobile shopping app usage

Consumers residing in different areas have varying levels of access to local retail stores. In contrast, with the prevalence of mobile internet, consumers have gained widespread access to mobile shopping. This research examines the impact of local offline retail density on consumers’ mobile shopping app usage and heterogeneity across consumer segments and different types of shopping apps. We use a unique dataset of individual-level mobile app usage with real-time location information across 1622 counties in China and employ the control function approach to address the endogenous retail density. Overall, the findings show that local offline retail density has a negative effect on mobile shopping app usage frequency and duration, indicating that consumers in areas with lower offline retail density engage more in mobile shopping app usage. This negative effect is weaker for consumers with higher mobility. Also, we find that this negative effect is weaker for shopping apps selling more technically complex products such as electronics than for those selling less technically complex products such as clothing and cosmetics. These results offer managerial implications for online retailers to launch targeting strategies to enhance consumer engagement with their shopping apps.

Monophasic Variant of Salmonella Typhimurium 4,[5],12:i:- (ACSSuGmTmpSxt Type) Outbreak in Central Italy Linked to the Consumption of a Roasted Pork Product (Porchetta).

The monophasic variant of S. Typhimurium 4,[5],12:i:- (MVST) is the third most commonly reported Salmonella serovar involved in human infections (8.8%) in the EU and ranks after S. Enteritidis (54.6%) and S. Typhimurium (11.4%). In Italy, in contrast, the MVST has achieved peculiar epidemiological and ecological success which has allowed it to be, since 2011, the serovar most frequently isolated from humans. In the summer of 2022, a foodborne outbreak of the MVST involving 63 people occurred in the Marche Region (Central Italy). A common food exposure source among some human cases was a roasted, ready-to-eat (RTE) pork product, porchetta, which is a typical product of Central Italy. This paper describes the results of investigations conducted to clarify this outbreak. The porchetta was produced by a local manufacturing plant and distributed to at least two local retail stores, one of which was the retail outlet for the manufacturing plant. The MVST was isolated from surface samples collected at the porchetta manufacturing plant and at both local retail stores via bacterial analysis, and the porchetta sampled at one store contained the MVST. These data confirm this type of RTE pork product can be a source of Salmonella infection in humans.

Evaluating the Release of Different Commercial Orally Modified Niacin Formulations In Vitro.

To evaluate the release profile of different modified-release oral formulations of niacin, such as immediate-release (IR) powder and tablets, timed-release (TR) caplets, extended-release (ER) capsules, and controlled-release (CR) tablets, to assure their defined release pattern and correlate this release with their matrix polymers. Niacin is used to manage hyperlipidemia by reducing cutaneous flushing and hepatotoxicity adverse events. The release profiles of different types of modified-release dosage forms depend on the types of coating materials (polymers) used in the matrix formation. Although different types of niacin formulations exist, none of the niacin dissolution profiles have been evaluated and compared in the literature. Four commercial orally modified-release niacin brands were collected from a local CVS pharmacy retail store, in Miami, FL, USA. The in vitro release study was conducted in simulated gastric fluid (SGF) and simulated intestinal fluid (SIF) conditions. The results of the release patterns of four niacin-modified dosage forms (IR, ER, TR, and CR) were aligned with their release definitions. However, the CR dosage form did not follow an ideal release pattern. The release rate of niacin in vitro was pH dependent, which was confirmed by the similarity factor (f2) results. All the f2 comparison values were below 50 in both the SIF and SGF media, while all the comparisons were below the f2 values for all brands in the SIF media.

The influence of social capital on local retail patronage in an urban setting

AbstractLocal retail stores are currently facing intense competition from both online retailers and large chain stores. An understanding of local retail store patronage (i.e., patronage of retail stores in one's own community) is essential to the survival and growth of local retailers. Drawing on Social Capital Theory, we theorize and show with store‐level survey data the influence of social capital (community attachment and reciprocity) on local retail store patronage in a large urban setting. We find that the impact of social factors differs for residents within the community compared to those outside of the community. We also demonstrate the importance of social factors in comparison to non‐social factors. These findings contribute to the literature by extending the impact of social capital on local retail store patronage beyond rural settings, providing insight into urban consumers' decision to patronize local retail stores, and highlighting the impact of community boundaries. These findings also generate practical recommendations for local merchants and stress the importance of building reciprocal relationships with local customers as well as varying communications across community boundaries.

TRACE ELEMENTS IN BREAKFAST FLAKES - BENEFITS AND RISKS ASSOCIATED WITH THEIR CONSUMPTION

Introduction. Breakfast flakes, contrary to their name, are eaten not only for breakfast, but also as snacks between meals. Children are considered to be the main consumers of flakes, but adults are also eager to choose this type of products. Such a great interest in breakfast flakes is, among others, due to a wide product range, the ease of preparation, low price and high content of nutrients, including trace elements. The aim of this study was to analyze the content of trace elements in breakfast flakes in terms of benefits and risks for consumers. Eleven types of breakfast flakes purchased at a local retail store were the material for the study. The analyses were carried out using ICP-AES (inductively coupled plasma atomic emission spectrometry) and GF-AAS (atomic absorption spectrometry with electrothermal atomization in a graphite cuvette). Results and conclusions. The analysis showed that the average iron content in all the analyzed flakes was 62.8 mg/kg, and the richest source of this element were multi-cereal flakes. Oatmeal was characterized by the largest amounts of zinc, copper and manganese. It was also noted that the consumption of a portion of oatmeal provides 57 % of the daily requirement of manganese for men and almost 73 % for women. Based on the results obtained, it was also found that the consumption of breakfast cereals does not pose a health risk related to the exposure of consumers to the adverse effects of elements supplied to the body while consuming these products.

Channel transparency and omnichannel retailing: The impact of sharing retail store product availability information

AbstractAs more firms look to implement omnichannel strategies to mitigate the inherent information barriers between online and offline channels, understanding the outcomes of these initiatives is critical. This study empirically examines the impact of the decision to share brick‐and‐mortar (B&M) store product availability information with customers, specifically focusing on the scenario where a discrepancy exists in the product assortment of online and offline channels. We investigate the impact of this information sharing strategy on customer research shopping trajectories using a proprietary dataset collected from a leading North American retailer. Using a difference‐in‐differences approach, we find that this strategy helps boost the overall sales from customers who reside within the trade area of a retail store. At the channel level, the policy induces customers to migrate from the B&M channel to the online channel after learning that the product selection offered at their local retail store may not meet their needs, resulting in a significant increase in online sales, but a slight decrease in B&M sales. From an operational perspective, our empirical evidence suggests that sharing retail store product availability information leads to more customers using the expedited shipping service when shopping online. Furthermore, we also discover a slight increase in the overall return rate. We conclude by providing managerial implications on the functionality of the online and B&M channels and how retailers can coordinate services offered by both channels to improve the utility customers receive from the brand.

In the Swim of Cannabis: Developmental Toxicity and Metabolomic Pathway Alterations of Zebrafish Larvae Exposed to THC for the Assessment of Its Potential Environmental and Human Health Impact.

As the pharmacological properties and therapeutic applications of Cannabis sativa L. pace with the upsurge of interest of the scientific community in harnessing its constituent phytocannabinoids, illicit use may raise serious health issues. Tetrahydrocannabinol (THC) is one of the most well-known phytoactive constituents of cannabis and continues to garner scientific and public attention not only because of its pharmacological value but also because over-the-counter products of THC and prescription medications are becoming increasingly available from pharmacies, dispensaries, Internet, local retail stores, or by illicit means. Hence, a multidimensional approach was employed to examine the impact of THC on zebrafish larvae. The acute toxicity, expressed as LC50, was 1.54 mg/L. Adverse effects were observed on the phenotype, such as tail bending, pericardial edema, etc., even at concentrations lower than LC50, and fundamental functions of larvae (e.g., heart rate and cardiac contractility, and rhythm) were significantly affected. Behavioral changes were noticed, which were reflected in locomotor activity and sensitivity to light/dark changes. Finally, an untargeted metabolomic study was carried out to shed light on the metabolic alterations that occurred, providing substantiating evidence of the observed phenotype alterations. Overall, the potentially detrimental effects of THC on a vertebrate model are depicted.

An Approach towards Deployable Hybrid Product Recommendation Systems for E-Commerce

As India is moving fast towards digital economy, E-commerce industry has been on rise. Many platforms provide their customers with a shopping experience better than actual physical stores. Several E-commerce websites use different methods to improve the customer engagement and revenue. One such technique is the use of personalized recommendation systems, which uses customer’s data like interests, purchase history, ratings to suggest new products, which they may like. Recom-mendation systems are used by E-commerce websites to suggest new products to their users. The products can be suggested based on the top merchants on the website, based on the interests of the user or based the past purchase pattern of the cus-tomer. Recommender systems are machine learning based systems that help users discover new products. Due to the recent pandemic situation of 2020 and 2021, many of the local retail stores have been trying to shift their business to online plat-forms such as dedicated websites or social media. The proposed methodology based on Machine Learning aims to enable local online retail business owners to enhance their customer engagement and revenue by providing users with personalized recommendations using past data using methods such as Collaborative Filtering, Popularity-based and Content-Based Filtering.

Donations for Refugee Crises: In-kind vs. Cash Assistance

Problem definition: Six million refugees have been living in camps in 2021 due to multiple armed conflicts worldwide. Regulations often impede refugees’ integration into host countries; thus, refugees have to seek help from humanitarian organizations (HOs). HOs traditionally provide in-kind (e.g., food) assistance and now offer cash (monetary assistance) that refugees can spend at local retail stores. However, cash assistance can be exploited by local retailers’ market power, which challenges HOs’ mission of helping refugees while doing no harm to host communities. Practical relevance: Completely informed by field research in three refugee camps in northwestern Greece, we analyze the trade-off between in-kind and cash assistance from the perspective of an HO. We propose two cash assistance policies, implementable by a partnership between the HO and the local government, to curb the retailer’s market power and ensure that the refugees, the local residents, and the retailer are better off than if only in-kind assistance is provided. Methodology: We use field research to define our research setting and support our main modeling assumptions and parameters. Then, we use a game-theoretical model to analyze the interactions among multiple stakeholders in an ecosystem consisting of an HO, refugees, a monopolistic retailer, local residents, and a local government. Results: We demonstrate the effectiveness of our proposed cash assistance policies that benefit refugees and local residents while ensuring the retailer’s profitability. In particular, a price-dependent cash assistance (PDCA) policy aligns the incentives between the retailer and the HO-government partnership. This new policy for cash assistance acts as a lever for the retailer to voluntarily set desirable prices, which benefit both refugees and their host community. Managerial implications: We provide tools and implementable policies that guide HOs to improve their budget allocation between in-kind and cash assistance for refugees living in areas where local market power exists. Moreover, we clearly outline the roles of HOs and the local government in a partnership for cash assistance to refugees. History: This paper has been accepted for the Manufacturing & Service Operations Management Special Section on Responsible Research in Operations Management. Funding: T. O. Kotsi thanks the Onassis Foundation (Greece) for financial support. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2021.1073 .

A Survey on Hybrid Recommendation Systems

As India is moving fast towards digital economy, E-commerce industry has been on rise. Many platforms such as Amazon and Flipkart provide their customers with a shopping experience better than actual physical stores. Several E-commerce websites use different methods to improve the customer engagement and revenue. One such technique is the use of personalized recommendation systems which uses customer’s data like interests, purchase history, ratings to suggest new products which they may like. Recommendation systems are used by E-commerce websites to suggest new products to their users. The products can be suggested based on the top merchants on the website, based on the interests of the user or based the past purchase pattern of the customer. Recommender systems are machine learning based systems that help users discover new products. Due to the recent pandemic situation of 2020 and 2021, many of the local retail stores have been trying to shift their business to online platforms such as dedicated websites or social media. The proposed methodology based on Machine Learning aims to enable local online retail business owners to enhance their customer engagement and revenue by providing users with personalized recommendations using past data using methods such as Collaborative Filtering and Content-Based Filtering.

A Study on Customer Perception Towards Supermarkets in Goa

People shift their buying from local retail stores to supermarkets, because of many reasons. This trend shift has not only been seen in metro cities but in small towns too. These change in perceptions of the customer insight the researcher and other stakeholder to study the reason behind it. This study tries to understand the demographic profile of the customers in Goa and compare the perception of customers towards supermarket and local retail stores. It has observed that people prefer supermarkets more as compared to the local retail store.

Pyrrolizidine alkaloid concentrations in local Italian and retail honeys of different origin: A scenario of human exposure

A validated method in liquid chromatography tandem mass spectrometry was applied to assess the contamination profile of 17 pyrrolizidine alkaloids and their N-oxide metabolites (PAs/PANOs) in 775 honey samples of different origins, including from local beekeepers (579, LB), large retail and online stores (Italian (LRI) and foreign (LRF) products). Fifty-five percent of the honey samples contained the 17 monitored compounds at below the limit of quantification. The LB samples were characterised by a total mean concentration of PAs/PANOs at 6.7 and 3.3 times lower than those of the LRF and LRI samples, respectively. The PA echimidine characterised mainly honey samples from the large retail stores (75.8 % and 72.5 % of LRI- and LRF-contaminated samples, respectively). The LB samples showed a senecionine-type contamination profile, providing beekeepers clues to the plants responsible for contamination. The results highlighted that the consumption of the local honey samples analysed does not represent a double risk for human health compared to the consumption of products from large retail stores. Careful attention must be paid to honey imported from areas where lycopsamine-type and senecionine-type PAs/PANOs-producing plants are invasive. A machine learning approach could predict the origin of the sample given its contaminant profile at an accuracy of 0.74, which is useful for detecting fraud in the declared honey origin.

Rohvi

Study level/applicability This case was successfully taught in a second-year MBA marketing course on the science of behavior change. It would be suitable for first-year MBA and executive education programs. The material would work well on courses on women in business, women as leaders and women in data science. The female protagonist creates a tech platform and uses a data-driven model. Subject area Marketing – it was used in a module around leveraging existing insights and creating new ones in marketing strategies. The course is structured around a “pathway to behavior change” framework. This case focuses on the analysis segment of the model, introduces targeted behavioral challenge(s) and lends itself to identifying consumer insights, biases and behaviors. It uses that analysis to learn about the market, competition and gaps to fill. Case overview This case uses a startup in the retail industry to explore the leverage of behavioral science to enrich a business model and structure a marketing campaign. The material unfolds the testing of an innovative process and use of persuasion to align business practices with human behavior and scale. In addition, it gives the opportunity to discuss how a minimal tech solution could bring in market data and provide a test platform to larger clients.The founder of Rohvi, Sara Whiffen, created a platform that allowed shoppers to buy clothing items from local retail stores, use them and after a few wears, return the items for partial store credit. The business model was based on Whiffen’s experience in the automobile industry with used cars. Following her first few years in the business, Whiffen had to make some decisions around engaging clients on two sides – retailers and consumers. How can an innovative startup leverage behavioral science to persuade multiple stakeholders? Expected learning outcomes • Learn marketing concepts in material and a tech platform featuring a female protagonist and team; • practice evaluating a product and capturing value using behavioral science; • understand consumer/business biases and practice forming and delivering a persuasive message; • learn to leverage and create new insights to aid behavior change in business-to-consumer (B2C) and business-to-business (B2B) contexts; • analyze behavioral insights to identify new opportunities in a competitive marketplace; • unfold a framework to explore consumer motivation in recommerce; and • explore the use of experimentation in changing consumer behavior and improving decision-making. Supplementary materials Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes. Social implications Females need to be represented in core business education curriculum such as data analysis in addition to classes focused on social equity and business. This all female executive team pursued an innovative process built on a technology platform using a data-driven model to gain enterprise clients. The material offers an opportunity to explore sustainability. Subject code CSS 8: Marketing

Histamine Level in Freshwater and Marine Fish Sold in Bulgarian Markets

Background: Histamine is an essential biogenic amine produced as a result of microbial decomposition of histidine during seafood processing and storage. The objective of this study was to evaluate histamine concentration in freshwater and marine fish marketed in Stara Zagora region, Bulgaria. Methods: Forty fish samples were purchased from local fish farms and retail stores in Stara Zagora, Bulgaria. Enzyme-Linked Immunosorbent Assay was used to determine histamine levels. The data were processed using GraphPad Software InStat 3. Results: Histamine was detected in 26 out of 40 (65%) samples, and none of them exceeded the regulatory limit of 200 mg/kg. The average histamine content in marine fish (6.965±3.187 mg/kg) was insignificantly (p>0.05) higher than that in freshwater fish (4.503±1.133 mg/kg). Conclusion: The results reveal low levels of histamine in freshwater and marine fish indicating their good quality. However, its presence in seafoods remains a major food safety problem that requires permanent regulation of histamine concentration in fish.

Understanding the customer psychology of impulse buying during COVID-19 pandemic: implications for retailers

PurposeDuring COVID-19 pandemic, the use of social media enhances information exchange at a global level; therefore, customers are more aware and make backup plans to take optimal decisions. This study explores the customer psychology of impulse buying during COVID-19 pandemic.Design/methodology/approachThe researcher, being a social constructionist, aims at understanding social patterns in impulsive buying strategies during COVID-19 pandemic. Forty UK consumers were participated using the telephonic interview method with the purpose to maintain social distancing practices.FindingsResults revealed that vulnerable group of people, fear of illness, fear of empty shelves, fear of price increase and social inclination to buy extra for staying at home, increased panic impulsive buying behaviour among customers. Many people socially interpreted the evidence of death rate and empty shelves, which led to more disinformation, rumours and sensationalism, which increased customers' impulsive buying behaviour. Finally, risk of going outside, COVID-19 outbreak among employees of local retail stores, and health professionals' recommendations to stay at home, led to impulsive buying behaviour.Originality/valueThis study has constructed a research framework of customer psychology of impulse buying based on the results of this study and fear and perceived risk theories. The study also explains how the fear of fear, risk perception and conformist tendency enhanced impulsive buying during COVID-19 pandemic. This study has discussed specific implications for retailers.

Reducing food waste through digital platforms: A quantification of cross-side network effects

To fight food waste, retail stores have begun selling perishable food close to the expiration date at discounted prices. To render this form of last-minute discounting effective, digital platforms have been developed with the major aim to connect local retail stores and their consumers by sharing information about these discounts. To sustain digital platforms, platform leaders need to ensure both consumers and retail stores remain active on it. To provide platform leaders with advice on how to create a sustainable digital platform, we examine how retail store activity on the digital platform affects consumer activity, and vice versa (also known as cross-side network effects). By combining a PVAR model and an impulse response function, along with data from a digital platform aimed at food waste reduction, we find that the effect of consumer activity on retail store activity is stronger and more long-lasting than the effect of retail store activity on consumer activity. We discuss the implications of our findings for both retail stores and digital platform leaders.

Simultaneous determination of mercury, cadmium and lead in fish sauce using Diffusive Gradients in Thin-films technique

Fish sauce is a popular seasoning liquid originating from southeastern Asian cuisine, consisting of fermented fish, salt and additional ingredients. Fish can contain high amounts of metals, some of which are hazardous for human health. Therefore, authorities responsible for food safety and quality should monitor the levels of these contaminants in fish and fish deviated products. In this work, the passive sampling technique of Diffusive Gradients in Thin-films (DGT) containing Chelex-100 and Purolite S924 resin gels, is used for the determination of dissolved mercury (Hg), cadmium (Cd) and lead (Pb) in fish sauce. The DGT performance test showed linear accumulation of Hg, Cd and Pb on the binding gels versus deployment time. A wide range of pH and salt concentration did not affect the performance of the DGT. The effective diffusion coefficients of Hg, Cd and Pb in diffusive gels were determined by applying a series of deployments in fish sauce solution. Besides the direct sampling with the DGT technique, fish sauce samples were also digested using a microwave oven. Analyses of DGT and microwave oven digested samples were performed with Sector Field Inductively Coupled Plasma Mass Spectrometry (SF-ICP-MS). Both methods were then used for the analysis of fish sauces from local retail stores. Due to the preconcentration ability of DGT, lower detection limits of Hg, Cd and Pb could be achieved compared to the microwave digestion method. The DGT technique offers a more sensitive method for trace element analysis in complex food matrices.