Sale Decisions Research Articles

Using social media for agricultural information dissemination: the role of informant-recipient homogeneity

ABSTRACT This study uses a randomised experiment targeting wheat producers in Ethiopia to examine the impact of providing market price information through Facebook on farmers’ sales behaviour. To identify the effect of informant homogeneity, we distinguished the informants’ nationality as either Ethiopian or foreign. Our findings reveal that when wheat selling prices were provided immediately after the harvest – when prices are typically at their lowest – only the information provided by Ethiopian informants led to a reduction in sales decisions and sales volume during that period. This information did not affect selling prices during the low-price period. However, analysis of data collected six months post-harvest shows that the selling price of wheat increased by approximately 14% due to information from Ethiopian informants. This suggests that farmers used the price information to delay sales until prices were higher, rather than negotiating with traders during the low-price period. Additionally, our heterogeneity analysis reveals that older, poorer, more socially isolated, and female farmers benefited more from domestic informant information, likely due to their previously limited access to information. These findings demonstrate the potential of social media for efficiently disseminating price information and highlight the importance of informant homogeneity in the effectiveness of such interventions.

Robust dynamic trading with realization utility

We incorporate model uncertainty into the intertemporal realized utility model proposed by Ingersoll and Jin (2013). We find: (1) model uncertainty erodes the investor’s value and makes him more willing to take the risk; (2) when ambiguity aversion is sufficiently high, voluntary realization of losses will not occur; (3) model uncertainty accelerates sales, thus shortening the average holding period and strengthening the disposition effect; (4) the disposition effect is weaker in the lower volatility case under model uncertainty, which is consistent with the empirical results; (5) model uncertainty alters the effect of volatility on the sale decision.

Research on Sales Decision of Vegetable Products Based on Time Series Analysis

Research on Sales Decision of Vegetable Products Based on Time Series Analysis

Research on the mechanism of leader-follower product sales competition based on market access restrictions and forward contract considerations

Market access restrictions have been the focus of attention for various market players, but there are fewer studies on the competitive mechanism of market access restrictions on firms' product sales. This paper investigates the competitive mechanism of leader-follower product sales based on market access restrictions and forward contracts. First, the mechanism of leader-follower sales decisions based on market access restrictions and forward contracts is clarified. Second, it models the forward default risk suffered by followers and the profit rate of leader-follower based on market access restrictions and forward considerations by Bayes' posterior probability method. Moreover, it severely explores the impact mechanisms of the degree of market access restrictions on leaders and followers when followers do not adopt and adopt forwards and makes a simulation analysis. The results show that: (i) When followers do not employ forward contracts, the less restrictive degree of market access increases the supply of leaders, and leaders' competition for product sales further leads to a decrease in the provision of followers. (ii) When followers use forwards, leaders' and followers' expected discounted profit rates decrease with the total supply of products in the market increases. (iii) If the degree of market access restrictions is low, the followers suffer an increased forward default risk, resulting in their rate of revenue decrease. The findings of this paper have some practical significance and policy implications for the regulator to adjust the degree of market access restriction in each restricted access area, to establish a reasonable and efficient competitive environment for product sales, as well as for firms to choose the optimal way of competing for product sales.

Mapping of community perspectives on land acquisition for biofuel investment in northern Ghana

We apply Q methodology, a model with a qualitative background, albeit with rigorous quantitative analysis, to map community perspectives (concerns, attitudes, beliefs, opinions, and perceptions) towards the acquisition of communal land for a biofuel project in northern Ghana. We extracted four community perspectives, in the order of importance as follows: (1) pro-biofuel project, but pessimistic (2) against the biofuel project (pro-environmental) (3) strong against and (4) optimistic. Taken together, the perspectives suggest the local people believe the biofuel project has no potential to improve their livelihoods, meanwhile, there is a consensus that the project destroyed trees of economic importance and provided poor working conditions for the local employees. We recommend (1) the establishment of enforceable economic and social contracts between the employees, local land users and the biofuel investors (2) direct monetary compensation for the affected communal land users (3) investigation of allegations of late or partial-payment of salaries of the biofuel project’s employees (4) future considerations for acquiring communal land should include broad community consultations and incorporate the local land users’ interests, concerns, and viewpoints and (5) the local bioenergy policy of the government of Ghana must include checks on communal land sale decisions, which directly or indirectly impact the welfare of the people.

Bank Resolution and the European Convention on Human Rights – A Note from the UK

Abstract This note considers human rights review of resolution decisions and processes – a context in which property rights can be limited or suspended given the operation of resolution decisions, including bail-in and sale decisions – in the context of the UK resolution regime and the relevance of the European Convention on Human Rights (the Convention) and the Charter of Fundamental Rights of the EU (the Charter) following the withdrawal of the UK from the EU. It outlines the UK framework, considers the current approach to rights review, and closes with the implications of the UK withdrawal from the EU on rights review, ex ante and ex post, against the Convention and Charter.

Price And Replenishment of Vegetables Based on NARX Neural Network

The research on the replenishment and pricing of vegetable commodities is helpful for supermarket to make more scientific purchase and sale decisions. Based on this, this paper mainly uses NARX neural network to study the replenishment and pricing of vegetable commodities. Firstly, it preprocesses the missing and abnormal values of the data, constructs a correlation analysis model to study the relationship between the sales of various categories of vegetables, then establishes a NARX neural network model to solve the daily replenishment total, and finally constructs a single objective programming model to get the pricing strategy, which provides a theoretical basis for supermarket to make scientific pricing and replenishment decisions.

Diffusion control in closed-loop supply chains: Successive product generations

We consider a durable-good producer who optimizes its sales decisions for two successive product generations with refurbishing and recycling potential. Customer arrivals follow a multi-generation diffusion process that takes into account the word-of-mouth feedback spread within each customer population of successive generations as well as the substitution effect among these generations. We investigate whether the producer can profit from partially satisfying the new-generation demand to slow down the product diffusion and improve the refurbishing and recycling volumes in the long run. We derive conditions for optimality of this partial-fulfillment policy. In fast-clockspeed industries, if the producer enters the refurbishing market for both generations, the partial-fulfillment policy is optimal if (i) the profit margin ratio of the early-generation product to the new-generation product is high enough, (ii) the profit margin ratio of the refurbished item to the new item is large enough for the new-generation product, and (iii) the fraction of customers willing to buy the refurbished item is only modestly large for each generation. If the producer uses the recycled content obtained from early-generation returns in new-generation production, the partial-fulfillment policy is optimal if (i) the number of early-generation end-of-life returns and the amount of recyclable material from each such return are large and (ii) the number of customers initially attracted by the early-generation product is high. We also characterize the critical time period beyond which initiating the partial-fulfillment policy provides no improvement in the refurbishing and recycling volumes for the new-generation product.

Utilization of the Geographic Information System Application in Making Sales Decisions at the Al2 Motor Store, Gorontalo Regency

The objectives of this research are: (1) to describe the availability of resources in decision making at AL 2 Shop, Gorontalo Regency, (2) to describe the factors inhibiting the use of the Geographic Information System application in decision making at AL 2 Shop, Gorontalo Regency. This research is qualitative research that is descriptive analysis using a phenomenological approach. The research results show: First, the availability of resources in decision making at AL Shop 2, Gorontalo Regency, including: (a) The computer hardware used includes labtops, chromebooks, printers and barcode scanners. (b) in terms of software, in utilizing this application, the Gorontalo Regency AL Motor Shop pays attention to several things, including: GIS, office, windows, (c) in terms of data and information, GIS has two interconnected data models, namely spatial data and nonspatial data.

NNBI: A Neural Network Based Business Intelligence Dashboard For A Clothing Store

Business Intelligence (BI) plays an important role in decision support systems by analyzing business data. Demand forecasting is a primary part of a sales decision system. In this research work, a Neural Network based Business Intelligence (NNBI) dashboard is proposed for a sales decision system. Data is collected from a leading clothing brand, then NNBI executes data and uses Recurrent Neural Network (RNN) to predict daily, monthly and weekly sales. The accuracy of the prediction model (0.95) validates the performance of NNBI. Tableau, a well-known BI tool is used to design NNBI dashboard. A combination of graphs, charts and text is used to interactively present the sales information. Results of NNBI show that a BI dashboard with the analysis and prediction power of NN is a good fit for a business organization.

Optimal pricing strategy of retailers considering speculative customers’ add-on items return behavior with cross-store full-reduction promotion

This purpose of the paper is to explore the optimal price strategy for the retailers under the cross-store full-reduction promotion mode, where speculative consumers will deliberately purchase add-on items to qualify for discounts when the purchase amount is less than the “full-reduction” threshold and then return the add-on items after successful payment. With respect to the optimal decision problem consisting of two online complementary retailers and an e-commerce platform in the face of speculative consumers’ add-on items return behavior, we construct the single-cycle sales decision models based on the revenue sharing contract. Furthermore, through the derivative function analysis method, we examine the effect of the proportion of speculative consumers, the proportion of product sharing discount amount and revenue sharing coefficient on the platform’s sale strategy and the retailers’ the optimal price strategy. The results show that whether platform implements cross-store full-reduction promotion strategy or not, the product price increases with the increase of revenue sharing coefficient. In addition, under the non-promotion sales mode, the optimal price is not affected by the speculative consumers’ behavior. Under the cross-store full-reduction promotion sales mode, the optimal price changes with the proportion of product sharing discount amount and the proportion of speculative consumers. And the price of only purchasing single product in this case is always higher than the price under the non-promotion sales mode. Finally, we compare the profits under the two scenarios, it is found that the profits under the cross-store full-reduction promotion sales mode are not always higher than that under non-promotion sales mode and the boundary conditions for the platform to adopt different modes are further given.

FACTORS INFLUENCING SALES DECISIONS AND THEIR IMPACT ON MICRO, SMALL AND MEDIUM ENTERPRISES IN BRAVO PHOTOCOPY BUSINESS BLANG PULO VILLAGE

This study aims to find out the sales decisions and their impact on micro, small and medium enterprises in the blang pulo village photocopy business. The research method used is the survey method. The survey research method uses data collection and analysis techniques in the form of opinions / facts from the subject under study (respondents) through question and answer which is directly communicated with the respondents, and interviews (oral questions) conducted with face-to-face communication. This research is qualitative which means descriptive research and tends to use analysis with an inductive approach.

Analisis Kualitas, Desain, Dan Harga Terhadap Keputusan Pembelian Sepatu Olahraga Produk NIKE Melalui Gaya Hidup Sebagai Variabel Intervening Di Kabupaten Sidoarjo

The purpose of this study is to conduct a Quality, Design and Price Analysis of the Purchasing Decision of Nike Sports Shoes Through Lifestyle as an Intervening Variable in Sidoarjo Regency. The research on Quality, Design and Price Analysis of the Decision to Purchase Nike Sports Shoes Products Through Lifestyle as an Intervening Variable in Sidoarjo Regency is to use quantitative methods in the form of surveys assisted by questionnaires and by using secondary data to become comparative materials. The sample used was 200 people who were determined by the purposive sample method in this case were users of Nike sports shoes with varying age ranges ranging from less than 20 years of age to 40 years. The analytical tools used are multiple linear regression test analysis, coefficient of determination (R2), correlation coefficient, and t test using the SPSS version 24 program. The result of this study is that product quality has a significant effect on purchasing decisions. Product design has a significant effect on sales decisions. The price of the product has an insignificant effect on sales decisions. Product quality through lifestyle does not have a significant effect on purchasing decisions. Product design through lifestyle has no significant effect on purchasing decisions. The price of products through lifestyle has a significant effect on purchasing decisions.

A farmer-centric agricultural decision support system for market dynamics in a volatile agricultural supply chain

PurposeIn a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.Design/methodology/approachThe present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.FindingsEmpirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.Practical implicationsAs a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.Originality/valueBased on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

Rancang Bangun Sistem Pendukung Keputusan Pemilihan Sales Terbaik pada PT Caturadiluhur Sentosa Menggunakan Metode SAW


 PT Caturadiluhur Sentosa Palembang is a company engaged in the distribution, logistics, and retail of building materials. PT Caturadiluhur Sentosa Palembang has several obstacles, namely the criteria for determining the best current sales by determining the largest turnover only. So that the current best sales appraisal system is considered less effective and unfair. The system built aims to build the best sales decision support system that can manage sales data and assessment parameters properly. The system built can manage sales data, criteria data, store sales appraisal data, and calculate sales value using the SAW method. The system is built using the iteration method. The result of this research is a decision support system that gives the best sales ranking based on the results of the assessment calculated using the SAW method.
 Keywords: Decision Support System, Iteration, SAW

Reference Dependence in the Housing Market

We quantify reference dependence and loss aversion in the housing market using rich Danish administrative data. Our structural model includes loss aversion, reference dependence, financial constraints, and a sale decision, and matches key nonparametric moments, including a “hockey stick” in listing prices with nominal gains, and bunching at zero realized nominal gains. Households derive substantial utility from gains over the original house purchase price; losses affect households roughly 2.5 times more than gains. The model helps explain the positive correlation between aggregate house prices and turnover, but cannot explain visible attenuation in reference dependence when households are more financially constrained. (JEL D12, D91, G51, R21, R31)

Product rollover and direct sales decisions in dual-channel supply chains

This study investigates product rollover and direct sales decisions in a supply chain with one fashion manufacturer and one retailer when two style generations are sequentially introduced to the market over two periods. The retailer serves as the exclusive sales channel during the introductory period of a style generation. Both the retailer and manufacturer are capable of selling the old style generation in the second period. The retailer adopts dual rollover if she sells the old style generation, and single rollover if she does not. We develop a two-stage game to explore the chain members’ equilibrium decisions while accounting for the manufacturer’s cost inefficiency in direct sales and consumers’ mental account deficit. We find that the manufacturer’s cost inefficiency has double-edged effects and can offset the negative effect of consumers’ mental account deficit on the introduction of a new style generation. Furthermore, a win–win outcome can be achieved when the manufacturer with an intermediate level of cost inefficiency engages in direct sales and consumers have high valuations of the old style generation or when the manufacturer with significant cost inefficiency does not engage in direct sales.

Trend Analysis in Sales Forecasting and Decision Support Systems AHP Method on the Selection of Types of Motorcycles PT. AHM

During the current Covid-19 pandemic, it has a direct impact on decreasing motorcycle sales at PT. Astra Honda Motor in large enough numbers, resulting in losses for the company. This study aims to analyze the forecasting of motorcycle sales in the future and supported by a decision support system in selecting the type of motorbike that consumers are most interested in. The method used in this research is the Trend method and the Analytical Hierarchy Process (AHP) method. The results of this study are based on the mean square error analysis, sales forecasting method at PT. Astra uses exponential trend analysis. The results of forecasting sales for the next 2 periods using the exponential trend analysis method are 2,715,032 units and 2,671,937 units, the sales levels tend to be the same as sales in the 2020 period. Meanwhile, the results of the decision support system analysis use the Analytical Hierarchy Process method (AHP), in choosing the type of motorbike that consumers are most interested in is an automatic motorbike at 0.63 with the preferred alternative is the fuel consumption aspect of 0.36.

Penerapan Data Mining Pengelompokan Menu Makanan dan Minuman Berdasarkan Tingkat Penjualan Menggunakan Metode K-Means

Data mining can be used to find solutions in making sales decisions to increase sales. Sales data storage stores many sales transaction records, where each document provides products purchased by customers in each sales transaction. A problem began to arise with an excess stockpiling of materials. The number of fluctuating sales causes the stock of available materials to be unstable and can directly impact consumers. Mistakes in predicting sales caused the coffee shop to buy large quantities of material stock, which were not widely used or sold out, so the supply of these materials swelled in the warehouse. One way to be implemented is by applying data mining because there are ways and methods to meet needs, one of which is the need for extensive information, then the information that we can use to determine quality in determining a decision. Therefore, it is hoped that this research can help Dpom Coffee minimize material stock inventory management cases such as shortages and excesses and make policies to increase sales by grouping menus based on sales levels using the K-means algorithm. Based on the results of processing the sales dataset at Dpom Coffee, it produces 3 clusters, namely Cluster 1 with eight menus with low sales levels, cluster 2 with 40 menus with moderate sales levels, and cluster 3 with seven menus with high sales levels. The accuracy or performance of the k-means algorithm results in a Davies Bouldin index value of 0.457.

Association Analysis with Apriori Algorithm for Electronic Sales Decision Support System

The purpose of this study was to determine the level of dependence of various items in order to dig up information on what items are dependent on other items. The method used in this research is descriptive analysis with a qualitative approach through a priori algorithm. The results show that the association analysis of the 26 transactions taken is 76.47%. A consumer who buys a laptop electronic device has the possibility to also buy an electronic mouse