Retail Stores Research Articles

Navigating Global Markets: Insights into Ceramic Firm Performance and Market Entry Strategies

Analyzing the intersection of market entry strategies and ceramic firm performance in the international market, this study offers insights into the dynamics shaping the competitiveness of U.S. ceramic firms abroad. By examining the strategic decisions guiding market selection and entry modes, this research sheds light on the factors influencing the success of ceramic enterprises on the global stage. This article delves into the intricacies of market entry strategies adopted by U.S. ceramic firms as they venture into international markets. It explores the strategic decisions made regarding market selection, distinguishing between English- and non-English-speaking countries, and the various modes of entry employed, including exporting, licensing, joint ventures, subsidiaries, and retail stores. The findings from a comprehensive analysis of 57 firms engaged in international markets unveil a significant trend: firms targeting culturally similar markets, particularly English-speaking ones, tend to achieve superior revenue generation and overall performance compared to those entering non-English-speaking countries. Additionally, through a cluster analysis, the study identifies four overarching modes of entry ranging from straightforward direct exporting to more intricate strategies integrating subsidiaries and retail outlets abroad. Surprisingly, the mode of entry doesn't exhibit a clear association with performance outcomes. This suggests a cautious approach by U.S. ceramic firms, opting for markets with lower levels of uncertainty, primarily through export activities.

The Influence of In-Store Recycling Signage on Consumer Behavior: A Study of Visual Attention and Usage of Store Drop-Off Bins

This study examined the impact of using three types of in-store signage to educate consumers about packaging recyclability as well as to measure its effectiveness in increasing awareness of a store drop-off recycling method for packaged granola. A total of 67 shoppers were recruited and divided into two groups to shop for granola in a retail store. Group A was not exposed to signage near the granola, while Group B was exposed to the in-store signage comprising shelf strips and aisle invaders with How2Recycle educational information containing messaging about the store drop-off recycling. A store drop-off bin was positioned at the entrance of the testing environment for both groups. The results showed that Group B had a significantly higher total fixation duration (p = 0.02) and fixation count (p = 0.03) than Group A in response to the recycling instructions on the drop-off bin. When comparing the three methods of in-store signage—shelf strips, aisle invaders, and the printed store drop-off bin panels—the shelf strips performed the best with regard to total fixation duration (1.72 s) and fixation count (5.91 counts) and were noticed by the highest percentage of shoppers. The store drop-off bin panels had the best performance with regard to time to first fixation (0.12 s). The aisle invaders had the lowest performance in all three eye tracking key metrics and were noticed by the lowest percentage of participants. These responses illustrate shopper challenges related to plastic recycling. This study demonstrates that recycling information can be effectively provided through strategically positioned in-store signage, especially messaging on shelf strips. While consumers are open to the usage of Store Drop-off Bins, affirming customer knowledge of these processes is essential to develop new consumer recycling habits.

A high density of ultra-processed food, alcohol & tobacco retail stores, and social inequalities are associated with higher mortality rates of non-communicable diseases in Mexican adults: 2005 to 2021.

Non-communicable diseases (NCDs) are the leading causes of mortality in Mexico. Factors contributing to NCDs-related deaths may vary across small geographic areas such as municipalities. We aimed to predict municipal-level factors associated with NCD mortality in Mexican adults from 2005 to 2021 using the small-area analysis (SSA) approach. We gathered data on population sociodemographic, access to healthcare services, and mortality records at the municipal-level from census and public institutions from 2005 to 2021. We identified municipal predictors of NCDs mortality rates (MR) using negative binomial regression models. A total of 584,052 observations of Mexican adults were analyzed. The national expected NCDs MR per 100,000 inhabitants was 210.7 (95%CI: 196.1-226.7) in 2005 and increased to 322.4 (95%CI: 300.3-346.4) by 2021. Predictors of NCDs mortality (quintile 5 vs. quintile 1) included; indigeneity (IRR = 1.15, 95%CI: 1.12-1.19), poverty (IRR = 1.14, 95%CI: 1.13-1.15), affiliation with Mexican Social Security Institute (IRR = 1.11, 95%CI: 1.09-1.14), households with television (IRR = 1.14, 95%CI: 1.11-1.17), and high density of ultra-processed food, alcohol & tobacco retail stores (IRR = 1.15, 95%CI: 1.13-1.17). The greatest increases in MR were observed in municipalities from Oaxaca (>200% increments). There was an overall increase in NCDs MR from 2005 to 2021, with a significant geographic variation among Mexican municipalities. The results of this study highlight the importance of identifying priority areas in the country that urgently require public policies focused on local factors associated with deaths from NCDs, such as the regulation of the ultra-processed food, alcohol & tobacco retail stores, and efforts to reduce social inequalities.

The Impact of Online Word of Mouth (e-WOM) on End-User Purchasing Intentions: A Study on e-WOM Channels’ Effects on the Saudi Hospitality Market

In this paper, we study the relationship between electronic word of mouth (e-WOM), brand perceptions, and consumer purchase intentions in the Saudi hospitality market via an extensive questionnaire design using a five-point Likert scale. A total of 410 respondents from the central, western, and eastern regions of Saudi Arabia were chosen using the convenience sampling technique. The structural equation modeling (SEM) analysis using SPSS AMOS 26 software showed that e-WOM via social media, online retail stores, brand-owned media, and influencers positively affects perceived brand quality, which leads to increased purchase intentions. The model showed an R-squared of 0.579, indicating that e-WOM explains about 57.9% of the variation in perceived brand quality. In particular, e-WOM through social media and influencers has been established as a strong factor in predicting perceptions of brand quality. This study reveals that learning the nuances and strategic management of e-WOM channels is key to improving brand perceptions and consumer purchase behavior in the Saudi hospitality market in the digital age.

A Comparative Study of Customer Perceptions: Organized Stores versus Kirana Stores in the Retail Landscape

This research aims to conduct a comprehensive comparative analysis of customer perceptions towards organized retail stores and traditional kirana stores. As the retail landscape undergoes transformation, understanding the factors that shape customer preferences and perceptions is crucial for both types of stores to effectively cater to consumer needs. Using a mixed-methods approach, this study combines qualitative insights gathered through interviews and focus group discussions with quantitative surveys to analyze and compare customer perceptions. Qualitative data will provide an in-depth understanding of the factors influencing customer opinions, while quantitative analysis will identify trends, preferences, and correlations among various aspects of organized and kirana stores. The research aims to uncover key determinants influencing customer choices, including the impact of the shopping experience, product availability, pricing strategies, convenience, and overall retail environment. Additionally, it seeks to identify areas for improvement and innovation within both types of stores by evaluating factors contributing to customer satisfaction and loyalty. The findings from this research are expected to offer valuable insights for retailers, policymakers, and industry analysts. By understanding the nuanced preferences of consumers in both organized and kirana retail settings, retailers can tailor their strategies to better meet customer expectations, fostering a competitive and adaptive retail environment. This study contributes to the broader understanding of consumer behavior in the evolving retail sector, providing a foundation for further research and strategic decision-making in the industry.

Seabream Quality Monitoring Throughout the Supply Chain Using a Portable Multispectral Imaging Device

Monitoring food quality throughout the supply chain in a rapid and cost-effective way allows on-time decision−making, reducing food waste, and increasing sustainability. A portable multispectral imaging sensor was used for the rapid prediction of microbiological quality of fish fillets. Seabream fillets, packaged either in aerobic or vacuum conditions, were collected from both aquaculture and retail stores, while images were also acquired both from the skin and the flesh side of the fish fillets. In parallel to image acquisition, the microbial quality was also estimated for each fish fillet. The data were used for the training of predictive artificial neural network (ANN) models for the estimation of total aerobic counts (TACs). Models were built separately for fish parts (i.e., skin, flesh) and packaging conditions and were validated using two approaches (i.e., validation with data partitioning and external validation using samples from retail stores). The performance of the ANN models for the validation set with data partitioning was similar for the data collected from the flesh (RMSE = 0.402–0.547) and the skin side (RMSE = 0.500–0.533) of the fish fillets. Similar performance also was obtained from validation of the models of the different packaging conditions (i.e., aerobic, vacuum). The prediction capability of the models combining both air and vacuum packaged samples (RMSE = 0.531) was slightly lower compared to the models trained and validated per packaging condition, individually (RMSE = 0.510, 0.516 in air and vacuum, respectively). The models tested with unknown samples (i.e., fish fillets from retail stores-external validation) showed poorer performance (RMSE = 1.061–1.414) compared to the models validated with data partitioning (RMSE = 0.402–0.547). Multispectral imaging sensor appeared to be efficient for the rapid assessment of the microbiological quality of fish fillets for all the different cases evaluated. Hence, these outcomes could be beneficial not only for the industry and food operators but also for the authorities and consumers.

E-fulfillment cost management in omnichannel retailing: An exploratory study

The purpose of this study is twofold: investigating how omnichannel (OC) retailers manage e-fulfillment costs and establishing how these costs relate to the evolution of OC retailers' e-fulfillment strategies. Experts in e-fulfillment from 34 European OC retailers across various sectors participated in an exploratory survey. The study's results reveal that although e-fulfillment costs significantly influence the evolution of e-fulfillment strategies, many OC retailers fulfilling online orders from retail stores or traditional warehouses remain unaware of the actual costs of e-fulfillment. Activities other than picking and last-mile delivery, such as inbound logistics and storage, are poorly controlled. Furthermore, complex cost metrics such as cost-to-serve—the total cost associated with delivering a specific order to a specific customer—are predominantly found among OC retailers operating fulfillment centers (FCs) in their e-fulfillment distribution networks. This underscores the need for all OC retailers to accurately assess e-fulfillment costs at multiple levels, which will be crucial for optimizing order preparation, tailoring pricing strategies, and achieving profitability, especially when operating hybrid e-fulfillment strategies where online orders are prepared in multiple facilities. As the largest study on e-fulfillment costs to date, it highlights the importance of advancing e-fulfillment cost management systems among OC retailers and adopting an approach that encompasses all e-fulfillment activities. Future research should delve into the key challenges of developing these systems, considering the operational realities of each OC retailer.

Influencing factors of spatial vitality in underground space around railway stations: A case study in Shanghai

Developing urban underground space for transportation and commercial purposes has become a vital strategy for sustainable urban growth, especially in dense urban contexts. The vitality of underground space has received wide attention as a key indicator of its efficiency and performance. The spatial vitality of underground space is affected by many factors, including function, spatial configuration, transport environment, and pedestrian-oriented design features. This study takes the underground space of Shanghai Hongqiao Business District (Phase I), one of the most successful integrated railway station-city development projects, as a case to explore the spatial and temporal distribution characteristics of spatial vitality and its influencing factors. Multilevel linear models were used to analyze the relationship between pedestrian flow and its influencing factors. Random forest models were used to investigate the relative importance of influencing factors on spatial vitality. This study verified that the distance to the transportation hub and spatial configurations calculated by space syntax are the two most essential factors for vitality. The number of retail stores and walkway width impact the vitality on weekends. The results shed light on our understanding of the urban vitality in the underground space and provide some tentative suggestions for the planning and design of underground space in high-density cities.

Comparative Analysis of use of Machine Learning Algorithm for Prediction of Sales

Predicting sales holds immense importance for businesses, particularly for large retailers. It significantly influences decision-making processes and their subsequent execution. For big retail stores engaged in marketing and sales, accurate sales prediction is crucial for effectively allocating resources, estimating sales revenue, and devising future strategies. It empowers these stores to grasp market trends, make informed decisions, and adapt to evolving conditions, ensuring long-term viability and prosperity. Given the dynamic nature of trends and market conditions, traditional forecasting methods face significant challenges in keeping pace with rapid changes. This is where the application of machine learning algorithms becomes indispensable, especially when dealing with large and complex datasets. This paper delves into the exploration of various machine learning algorithms and models to predict sales, conducting comparative analyses to assess their performance.The overarching aim is to identify the most suitable algorithm or combination of algorithms through comprehensive analysis. Furthermore, the paper scrutinizes how the characteristics of the dataset impact the performance of these algorithms, offering valuable insights for selecting the most appropriate machine learning algorithm based on performance analysis. By leveraging these insights, businesses can enhance their sales prediction capabilities and make informed decisions, thereby maximizing their success in the marketplace.

Offline Returns for Online Retailers via Partnership

Online shoppers often prefer to return items to stores (i.e., “offline return”) rather than mail them back. We study a new business practice, return partnership, wherein online retailers partner with store retailers to offer offline returns. We seek to identify when return partnerships benefit both the store and online retailers. Customers choose between the online and store channels for their purchase and decide whether, and through which channel, to return an online purchase if needed. We find that store and online retailers who offer differentiated products have incentives to partner, as in the case of the return partnership between Everlane and Cost Plus World Market (formed via Happy Returns—a service provider that connects online retailers with store retailers). In this case, the online retailer’s benefit from the cost savings achieved by consolidating shipments of returned items from stores outweighs the loss associated with a high return rate. We show that, contrary to initial intuition, return partnerships may also feature retailers who offer similar products, as in the case of Amazon-Kohl’s. In this case, online customers’ migration to offline returns ensures a store retailer’s incentive to partner. However, it limits the incentive of an online retailer when the added convenience of an offline return induces more returns of online purchases. Thus, we caution that with limited differentiation in product offerings, store visits should not be too convenient for a partnership to form. This paper was accepted by Jay Swaminathan, operations management. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.01291 .

Unraveling the Effect of Marketing Mix 7P on Consumer Purchasing Decisions: A Study of Gerai Daging Online Store at PT. XYZ

Nowadays the internet presence allows the exchange of information and communication flows that are not limited by time and space. The increasing number of internet users in Indonesia has led to a new trend globally, which is the online shopping trend. PT XYZ (Persero) is one of Indonesia's state-owned enterprises engaged in the livestock sector. PT XYZ has a retail store that sells livestock products, both fresh dan processed. A marketing mix is a tool that can be used by companies to achieve marketing goals in target markets. The objective of this study is to determine the influence of marketing mix 7p (product, price, promotion, people, process, physical evidence, and place) on consumer purchase decisions at the Gerai Daging online store XYZ. This research used 55 respondents with a purposive sampling technique. The research was conducted by distributing questionnaires to respondents. Data were analyzed using SPSS Version 25 software with multiple regression analysis. The results show that marketing mix 7P which consists of 7 attributes, namely product, price, promotion, people, process, physical evidence, and place, didn't show any influence on purchasing decisions at Gerai Daging online store PT. XYZ either simultaneously or partially.

The effects of motivation and prior knowledge on wine consumers’ decision-making process: using an extended model of goal-directed behavior

PurposeThis study aims to use the extended model of goal-directed behavior (EMGB) to examine the interaction between wine purchasing motivations and prior knowledge and their impact on consumers’ wine purchase intentions and decisions.Design/methodology/approachThe survey was conducted in large discount retail stores in South Korea, and structural equation modeling analysis reveals EMGB’s strong predictive ability to understand wine buying behavior.FindingsNotably, the findings reveal that social life and enjoyment motivations play a significant role in shaping consumers' attitudes. In addition, positive emotions, attitudes, prior knowledge, subjective norms and negative anticipated emotions all have a positive effect on desire, while desire, prior knowledge and frequency of past behavior have a significant impact on behavioral intention. Contrary to previous studies, celebration motivation has no significant effect on attitude and perceived behavioral control has no significant effect on desire and behavioral intention.Research limitations/implicationsThe findings provide practical insights for marketers to conduct targeted wine marketing campaigns and increase consumers' intention to purchase wine.Originality/valueThis study furthers the understanding of the complex mechanisms involved in shaping the intention to purchase wine using the EMGB framework.

Emerging market's consumer intention towards the use of eco-friendly shopping bags in retail stores

The purpose of this study was to explore variables explaining consumers' intention toward the use of eco-friendly bags in retail stores in an emerging market economy, Thailand. The research was hinged on the Theory of Planned Behavior. The study adopted a survey research design where data was collected using a structured questionnaire on a 5-point Likert scale, with the study sample selected by convenience and purposive sampling methods. The sample population consisted of 609 Thai consumers aged 18 years and above who have shopped in retail stores. Multiple linear regression analysis was applied to analyze the data. The results revealed that environmental attitude, subjective norms, and perceived behavioral control had a positive effect on consumer intention towards the use of eco-friendly shopping bags in retail stores. Whereas subjective norms had the highest effect on consumer intention towards the use of the eco-friendly bag in retail stores. The findings of this study are expected to help the government and private sector to create an appropriate marketing tactics such as using influencers to increase consumer intention towards the use of an eco-friendly bag.

Visual Communication of Festive Shop Window Displays with Customers

The object of the authors’ research was the festive Christmas window displays of brick-and-mortar retail stores. The main objective of the research was to identify the dominant colours, symbols and signage of Christmas festive displays of retail brick-and-mortar stores across different product categories and countries around the world. A total of 229 retail Christmas window displays, from 14 countries around the world, across 11 assortment categories, ready for the Christmas season in 2020, 2021 and 2022, were examined. The theme of Christmas resonates in retail store windows from the beginning of November until 24 December. After this date, the issue of sales dominates the window displays. The main method of the research was the content analysis used to analyse the documents in order to determine the frequency of occurrence of the pre-given categories. Given that our interpretation of Christmas is based on its Christian foundation, it is not surprising that the main universal colours and symbols of interpretation identified are rooted in Christianity, while other, complementary ones (e.g. Santa Claus with a reindeer sleigh, a snowy landscape, or a gingerbread house) and the signage are the result of changes in popular culture over time.

EXPLORATORY ANALYSIS WITH ASSOCIATION RULE MINING ALGORITHMS IN THE RETAIL INDUSTRY

Every year the retail sector expands quickly. These industries are becoming more competitive and difficult to operate in due to their expansion. Changing consumer buying habits, a decline in people's spending capacity and an increase in international retailers are a few of the difficulties that must be overcome. In the context of mining frequent item sets, many methods have been proposed to push various kinds of limitations inside the most well-known algorithms. This study presents an exploratory analysis for retail stores that uses market basket analysis as one of the data mining techniques to identify frequent patterns in customer purchases. The proposed method is based on comparing two algorithms: Apriori and Frequent Pattern Growth (FP- Growth). The study used a retail store dataset consisting of 522,064 rows and 7 variables. Data pre-processing was performed to clean and encode the data to be used in the model. The dataset limitation involves 25% null values in the ID column. To address this, missing customer IDs are filled with the last valid ID, assuming repeated purchases. The FP-Growth algorithm was found to be faster and more effective than the Apriori algorithm in extracting frequent item sets and generating association rules. The retail industry based on these frequent item sets is expected to increase sales by recommending highly associated items to customers.

Barriers to the implementation of energy-efficiency practices in the U.S. retail sector: facilities managers’ perceptions compared by facility size and business revenue

PurposeThe retail sector has the largest energy consumption among commercial buildings in the U.S. Although previous studies explored benefits, barriers and solutions for implementing sustainability in various building sectors, research focused on retail facilities has been very scarce. This study aims to explore U.S. facilities managers’ perceptions of barriers that prevented the implementation of energy-efficiency practices in the retail sector. Their perceptions were compared by facility size and facilities management company’s business revenue.Design/methodology/approachAn online survey was distributed to the members of the International Facility Management Association and the author's LinkedIn network. The survey responses were analyzed using descriptive statistical analysis and ANOVA.FindingsManagers from large facilities, as opposed to those from small ones, significantly more agreed that the unavailability of building automation systems, a lack of professional writing skills and a lack of awareness of life cycle cost (LCC) were the barriers. Business revenue did not cause significantly different perceptions of the barriers except for a lack of awareness of LCC and a lack of support from upper management.Originality/valueThis study fills the research gap on energy efficiency in the retail sector by revealing U.S. facilities managers’ perceptions of the barriers to the implementation of energy-efficiency practices in retail stores. This novel study compares perceptions of the facilities managers by facility size and business revenue; this comparison has not been performed before. The study also identified several new barriers to the implementation of energy efficiency in the retail sector.

What Message Does Wine Send to the Consumer Through the Label

Abstract Wine is a complex product that goes from the concept of food to that of hedonic drink in the perception of consumers. In this context, it is very important for wine producers to understand the factors of perception of consumer quality but also the relative importance they attach to these factors when deducting the quality of wine to meet these expectations, needs or desires. The existing label on a bottle of wine must contain practical and accurate information so that the consumer makes the purchase decision instead of a similar products. Buying wine in the retail store system (specialized stores) should not hurt more than ten minutes (2003, Schnettler and Rivera). So, both the information on the label and the product evaluation will be closely related to the time consumers need to observe and analyze them (2017, Krishna et al.). If we include the information such as: the designation of origin, therapeutic recommendations, nutritional information, have a great influence on the intention to purchase and as a result this aspect requires in-depth studies. Content is especially important for experienced consumers who are looking for relevant information available to be sure of their purchase. This article presents importance to wine specialists, experts, research, as a starting point in understanding information about consumers behavior for the same products and markets. They can be used as a guide to identify similarities in consumer behaviors for different products with wine-like features. We aim to complement this research with recent findings and conclusions related to consumer behavior by studying culture and noting differences in the country, culture, religions or races in wine consumption. We can provide a general picture of the current state of education of the factors of perception of wine quality through sensory analysis. To this end, the factors determining the perceived state of the wine as a product, the state of the consumer and the state of consumption shall be analyzed first. Then, the most widely used methodologies are discussed to study the hedonic sense of consumers. Finally, the characteristics of wine related to the perception of the quality are evaluated.

Agreement between a web collaborative dataset and an administrative dataset to assess the retail food environment in Mexico

BackgroundLatin American countries are often limited in the availability of food outlet data. There is a need to use online search engines that allow the identification of food outlets and assess their agreement with field observations. We aimed to assess the agreement in the density of food outlets provided by a web collaborative data (Google) against the density obtained from an administrative registry. We also determined whether the agreement differed by type of food outlet and by area-level socioeconomic deprivation.MethodsIn this cross-sectional study, we analyzed 1,693 census tracts from the municipalities of Hermosillo, Leon, Oaxaca de Juarez, and Tlalpan. The Google service was used to develop a tool for the automatic acquisition of food outlet data. To assess agreement, we compared food outlet densities obtained with Google against those registered in the National Statistical Directory of Economic Units (DENUE). Continuous densities were assessed using Bland–Altman plots and concordance correlation coefficient (CCC), while agreement across tertiles of density was estimated using weighted kappa.ResultsThe CCC indicated a strong correlation between Google and DENUE in the overall sample (0.75); by food outlet, most of the correlations were from negligible (0.08) to moderate (0.58). The CCC showed a weaker correlation as deprivation increased. Weighted kappa indicated substantial agreement between Google and DENUE across all census tracts (0.64). By type of food outlet, the weighted kappa showed substantial agreement for restaurants (0.69) and specialty food stores (0.68); the agreement was moderate for convenience stores/small food retail stores (0.49) and fair for candy/ice cream stores (0.30). Weighted kappa indicated substantial agreement in low-deprivation areas (0.63); in very high-deprivation areas, the agreement was moderate (0.42).ConclusionsGoogle could be useful in assessing fixed food outlet densities as a categorical indicator, especially for some establishments, like specialty food stores and restaurants. The data could also be informative of the availability of fixed food outlets, particularly in less deprived areas.

Analyzing the Role of Utilitarian and Hedonic Values on Customer’s Repeat Purchase Intention in Online Shopping

Consumer buying behavior has recently become a topic of discussion in both developing countries and under developing. Marketers, researchers, supply chain analyst, and policy maker everyone is paying special attention on this. Due to complex nature of human and decision making process many countries are still working to understand this phenomenon. Using Mean End Chain (MEC) theory, the goal of this study is to examine how hedonic and utilitarian values, as well as issues with e-service and product quality, affect customers' intentions to make more purchases when they buy online. Data were gathered from 209 universities students through online Google survey form. SPSS and smart PLS were used to analyze the collected data. The finding of this research demonstrated that hedonic value and utilitarian value both have a significant impact on repeat purchase intention. An e-service quality is contributing in different ways. Lastly the quality of a product is influencing the customer to repeat customer i.e. if the product is according to the demand of customer so they will rebuy the product. The findings of this paper will help marketers and supply chain experts in their fields specially the one who owns a retail store. This paper will guide them to develop and implement such practices that would force the customer to retained customer/ repeat customer.

Hybrid Distribution Model and Market Penetration of Consumer Electronics in Nigeria

In a geographically large and diverse market like Nigeria, gaining full-scale market penetration for consumer goods can be a herculean task due to inadequate transportation infrastructure, and lack of robust channel structure. This study sought to mitigate this challenge by investigating the causality between hybrid distribution model and market penetration. It specifically aimed to determine the influences of direct and indirect distribution on market penetration of consumer electronics in Nigeria. The study adopted cross-sectional research design. Primary data were obtained from 384 major distributors of consumer electronics in Port Harcourt, Calabar and Ikeja through a structured questionnaire. Snowball and quota sampling techniques were applied to recruit respondents for the survey. The data obtained were analyzed using descriptive statistics and the hypotheses of the study were tested using multiple linear regression. The findings of the study revealed that even though both direct and indirect distribution strategies had significant positive influences on market penetration of consumer electronics in Nigeria, the indirect distribution approach had a higher contribution to market penetration. Hence, the study concluded that hybrid distribution model strategically enhances the ability of manufacturers of consumer electronics to achieve extended market penetration in Nigeria. Therefore, we recommended that: manufacturers of consumer electronics should establish direct distribution outlets in Nigeria such as company warehouses, manufacturer-owned retail stores, corporate online stores, and direct sales representatives in order to effectively sell products to customers while eliminating the prospects of third-party adulterations, counterfeiting and other unwholesome practices of middlemen; and there is need for manufacturers of consumer electronics to collaborate and strategically partner with capable intermediaries like wholesale distributors, retail chain stores, independent retailers, online marketplaces, authorized dealers and market traders to achieve extended market coverage and ensure their products are extensively available in the Nigerian market.