Applications of a geographic information system–based business intelligence system for decision making at Coffee Refresh

This case is designed to illustrate how to utilize a business intelligence framework and a geographic information system to make better decisions on franchise opening requests. The case started when Jong, the senior certified analytics professional, and his team were drafting a proposal presentation on a new franchise approval process to present to Tony, the director of Coffee Refresh. Currently, Coffee Refresh was experiencing a significant delay in approving franchise opening requests. In addition, the current approval process was relied on the appraisal teams’ evaluations, which involved self-judgment as to the accessibility and visibility of the store location in each franchise opening request and a manual count of the potential targeted customers at each location, which impacted how the appraisal teams estimated the expected revenue for each location. During the first meeting with Jong and his team, Tony was frustrated by the current evaluation process, resulting in a significant backlog of requests pending approval, which was far behind the target for its franchise branch expansion strategy. It had also been reported that the branches that opened during the past few years had a relatively low success ratio (losses between 4.8% and 16.5%) and that the rate of branch closures had increased from 2% to 7.5%. Currently, eight franchise opening requests were pending, and Jong had to provide a recommendation for which requests should be approved. Coffee Refresh could approve all of them instantly, approve some of them, or even decline all of them. This was a great opportunity for Jong and his team to revisit the current franchise approval process and to demonstrate how business intelligence systems could improve the request approval process as well as address the issues of the current franchises’ underperformance and the closure rates.

PEMBUATAN APLIKASI ECOMMERCE USAHA MIKRO KECIL DAN MENENGAH (UMKM) WAROENG BU DHEVI

Usaha Mikro Kecil dan menengah (UMKM) are one of the micro businesses that empower home industries. Indonesian UMKMs have a contribution of 15.8% to the global production supply chain at the ASEAN level. The development of MSMEs from year to year is influenced by the use of information technology and information systems. E-commerce is one of the technologies that support the development of SMEs and trade today. The number of Micro, Small and Medium Enterprises (UMKMs) joining e-commerce is increasing. Until August 2021, more than 14 million UMKMs or 22 percent of the total UMKMs have joined the e-commerce electronic trading application. UMKM Waroeng Bu Dhev was established on 27 February 2020 and is located at Bumi Menteng AsriHousing Complex, Jl. Therapy IIa BA 8, RT01/17 Bogor. Engaged in the business of making and selling various foods, such as Lapis Maksuba, Lapis Engkak, Dimsum, Choipan, Pastries, Kastengles, Nastar and so on. Currently, Waroeng Bu Dhev's marketing is still using the traditional method, namely word of mouth. There has been no marketing effort through promotional activities and sales using other media. The purpose of this Community Service activity is to help develop Waroeng Bu Dhev SMEs through e-commerce promotion media, especially in terms ofproduct promotion and sales. The ecomerce design method uses a prototyping software application, namely by involving the user iteratively in each design phase. The e-commerce application built consists of 9 menus, namely: Shop, Update & Promo, Store Location, FAQ, Search Products, Your Account, Your Cart, [email protected], and WHATSAPP.Usaha Mikro Kecil dan menengah (UMKM) merupakan salah satu usaha mikro yang memberdayakan industri rumahan. UMKM Indonesia memiliki kontribusi sebesar 15.8% terhadap rantai pasok produksi global di tingkat ASEAN. Perkembangan UMKM dari tahun ke tahun dipengaruhi dengan pemanfaatan teknologi informasi dan sistem informasi. E-commerce merupakan salah satu teknologi yang mendukung perkembangan UMKM dan perdagangan saat ini. jumlah Usaha Mikro, Kecil, dan Menengah (UMKM) yang bergabung dengan e-commercesemakin meningkat. Sampai Agustus tahun 2021 sudah lebih dari 14 juta UMKM atau 22 persen dari total UMKM, yang sudah bergabung dengan aplikasi perdagangan elektronik e-commerce. UMKM Waroeng Bu Dhev berdiri sejak tanggal 27 februari 2020 dan berlokasi di Perumahan Bumi Menteng Asri Jl. Terapi IIa BA 8, RT01/17 Bogor. Bergerak dalam bidang usaha pembuatan dan penjualan aneka makanan, seperti Lapis Maksuba, Lapis Engkak, Dimsum, Choipan, Kue kering, Kastengles, Nastar dan sebagainya. Pemasaran yang dilakuan Waroeng Bu Dhev saat ini masih melalui cara tradisional, yaitu dari mulut ke mulut. Belum ada upaya pemasaran melalui kegiatan promosi dan penjualan menggunakan media lainnya. Tujuan kegiatan Pengabdian kepada Masyarakat ini adalahmembantu pengembangan UMKM Waroeng Bu Dhev melalui media promosi ecommerce, khususnya dalam hal promosi dan penjualan produk. Metode perancangan ecoomerce menggunakan aplikasi perangkat lunak prototyping, yaitu dengan melibatkan user secara iteratif pada setiap fase perancangan. Aplikasi ecommerce yang dibangun terdiri dari 9 menu, yaitu: Shop, Update & Promo, Lokasi Toko, FAQ, Search Products, Your Account, Your Cart, [email protected], dan WHATSAPP.

Importance of Marketing Mix Elements in Determining Consumer Purchase Decision in the Retail Market

This research aimed to identify the linkages between marketing mix elements and the purchase decision process among consumers in the Malaysian retail industry. To fulfill this objective, the present study followed a quantitative survey for gathering the data from the consumers of department stores at the East Coast region in Malaysia. All of the obtained data were inserted and coded using SPSS and then analysed by AMOS 18. The findings indicated that the impact of advertising on the consumers' purchase decision is positive and statistically significant. Besides that, the findings demonstrated that distribution intensity has a negative effect on purchase decision, whereas price plays a key important role in affecting purchase decisions process of the consumers. Lastly, the findings of this paper verified that store image and store location have significant positive linkages with purchase decision. These outcomes enhance our understanding on the role of marketing mix elements in determining a consumer's purchase decision, particularly in the retail context.

The economic resilience of amenity cluster in the post-Covid city: the effect of relatedness on the survival of amenity shops

Amenity clusters that consist of coffee shops, restaurants, and other small businesses provide utility to urban life and jobs for city dwellers. While most small business clusters were hard hit by the restrictions imposed during the COVID-19 pandemic, others were able to adapt. What determines the economic resilience of amenity clusters? By using store-location data for Seoul during 2016-2021, we identify spatial clusters of amenities and an \textit{amenity space} to examine the effect of relatedness on the resilience of each cluster. We find that businesses are more likely to survive when located in clusters of related amenities.

Food Insecurity and Food Label Comprehension among Libyan Migrants in Australia

Food security among migrants and refugees remains an international public health issue. However, research among ethnic minorities in Australia is relatively low. This study explored the factors that influence the understanding of food labelling and food insecurity among Libyan migrants in Australia. An online survey was completed by 271 Libyan migrant families. Data collection included the 18-item US Household Food Security Survey Module (for food security) and a question from the Food Standards Australia New Zealand Consumer Label Survey (for food labelling comprehension). Multivariable logistic regression modelling was utilised to identify the predictors of food label comprehension and food security. Food insecurity prevalence was 72.7% (n = 196) while 35.8% of families (n = 97) reported limited food label understanding. Household size, food store location, and food affordability were found to be significantly related to food insecurity. However, gender, private health insurance, household annual income, education, and food store type and location were found to be significantly related to food labelling comprehension. Despite the population’s high educational status and food labelling comprehension level, food insecurity remained an issue among the Libyan migrants. Policy makers should consider the incorporation of food label comprehension within a broader food security approach for migrants.

EVALUATING THE ACCURACY OF POST-PROCESSED KINEMATIC (PPK) POSITIONING TECHNIQUE

Post-processing kinematics (PPK) is positioning process in which signals received from a mobile receiving device store location data can be adjusted using corrections from a reference station after data has been collected. The processed kinematic screening method provides the surveyor with a technique for high production survey measurements and can be used in areas with minimal satellite barriers. PPK uses significantly reduced observation times compared to static or fast static observations. This method requires least squares adjustment or another multiple basic statistical analysis that can produce a weighted average of observations. The results obtained using PPK are between 1 cm and 3 cm for horizontal coordinates and from 1 cm to 10 cm for vertical coordinates.

Community-Based Efforts Aim to Improve the Food Environment within a Highly Obese Rural Appalachian County

Rural communities in Appalachia are displaying increased obesity prevalence, yet traditional interventions have not provided a broad enough impact to improve dietary consumption patterns. Therefore, expanding efforts that address the food environment and incorporate behavioral nudges through community-developed marketing strategies may be a viable mechanism to improve food and beverage choices within this unique population. This study installed shelf-wobblers across n = 5 gas stations in one rural Appalachian county in Kentucky. Smart Snacks were identified from store inventory lists utilizing the CDC Food Service Guideline for Federal Facilities calculator and were categorized into high-protein snacks, low-fat carbohydrate snacks, meal replacement snacks, and no-calorie beverages. NEMS-CS audits were conducted, and monthly sales data was collected at baseline and for six months thereafter for each store location. A difference-in-difference model was used, adjusting for total sales or total mean sales for each Smart Snack model to assess the percentage change within and between stores. Overall, percent change in mean sales and total sales across all stores resulted in a percentage increase of sales of Smart Snack items following wobbler installment. This study provides unique insight into how a community-driven approach to marketing can influence the sale of healthier food and beverage items.

An Analysis of Major Retail Store Change in Canada: 2013-2018

International retail has experienced significant numbers of closures in bricks-and-mortar stores in recent years. Moreover, with substantial reporting’s on international closures, there has been a notable absence for reports on Canadian retail as a whole in relation to store closures. Therefore, this research is a location-based analysis on where retail closures are in Canada. The objectives are: (1) to examine the store changes taking place in Canada through analysis of a selected subset of retailers; (2) to assess the influence of omni channel activities on store location strategies; and (3) to discuss the implications of store change with regard to the future of physical ‘bricks-and-mortar’ retailing in Canada. This major research paper utilizes a store per capita analysis to understand where closures in retail are in relation to population markets of varying sizes. The data utilized is from the Centre for Study of Commercial Activity, consisting of every physical store location between 2013 and 2018 for a set of twelve specifically selected retailers. The results of this paper are compared between the retailers respective retail sectors and supplementary retail quadrants they were assigned to.

An Analysis of Major Retail Store Change in Canada: 2013-2018

International retail has experienced significant numbers of closures in bricks-and-mortar stores in recent years. Moreover, with substantial reporting’s on international closures, there has been a notable absence for reports on Canadian retail as a whole in relation to store closures. Therefore, this research is a location-based analysis on where retail closures are in Canada. The objectives are: (1) to examine the store changes taking place in Canada through analysis of a selected subset of retailers; (2) to assess the influence of omni channel activities on store location strategies; and (3) to discuss the implications of store change with regard to the future of physical ‘bricks-and-mortar’ retailing in Canada. This major research paper utilizes a store per capita analysis to understand where closures in retail are in relation to population markets of varying sizes. The data utilized is from the Centre for Study of Commercial Activity, consisting of every physical store location between 2013 and 2018 for a set of twelve specifically selected retailers. The results of this paper are compared between the retailers respective retail sectors and supplementary retail quadrants they were assigned to.

Perbandingan Algoritma Machine Learning dalam Menilai Sebuah Lokasi Toko Ritel

— The application of machine learning technology in various industrial fields is currently developing rapidly, including in the retail industry. This study aims to find the most accurate algorithmic model so that it can be used to help retailers choose a store location more precisely. By using several methods such as Pearson Correlation, Chi-Square Features, Recursive Feature Elimination and Tree-based to select features (predictive variables). These features are then used to train and build models using 6 different classification algorithms such as Logistic Regression, K Nearest Neighbor (KNN), Decision Tree, Random Forest, Support Vector Machine (SVM) and Neural Network to classify whether a location is recommended or not as a new store location. Keywords— Application of Machine Learning, Pearson Correlation, Random Forest, Neural Network, Logistic Regression.