Customer Habits Research Articles

Exploring Factors Influencing Customers Decision Making towards Online Grocery Retail Services in Kolkata

Online grocery retail services are a new trend in Indian urban cities. The two large players namely Grofersand Big Basket attracting customers. The study is an attempt to understand the changing scenario in grocery retail sector. The prime objective of the study is to explore the factors that are attracting customers to choose e retail for Groceries. The data was collected through questionnaire from 100 respondents. Factor analysis (Principle Component Analysis method) was used to explore the influencing factors. These results have shown that mainly customer service, convenience, loyalty rewards, product vailability and payment options are attracting the customers to choose Grophers and Big Basket. These companies have a huge untapped markets and will easily convert the habits of customers in Urban areas.

Channel Habits and the Development of Successful Customer-Firm Relationships in Services

Technology advances have profoundly changed the way customers and service organizations interact, leading to a multitude of service channels. This study investigates consumer habits toward service channels in order to understand the influence of these channel habits on perceptions and intentions (perceived switching costs and attitudinal loyalty) and on consumer behavior (service usage and cross-buy). We empirically test the framework in the financial services industry, and the results reveal that physical store habit increases perceived switching costs and that acquired habits toward the physical store and self-service kiosks have a positive influence on attitudinal loyalty. Perceived switching costs positively affect service usage, and attitudinal loyalty positively influences cross-buy. In addition, habits in each channel lead to an increase in the number of services acquired (cross-buy), but online and self-service kiosks channel habits negatively impact service usage, as the lack of physical presence may increase customer uncertainty. Because habits are built on the frequency and stability of channel usage, firms can manage habits by encouraging frequent interactions under stable contexts. In addition, firms should stimulate customer habits toward the physical store as it is central to the promotion of loyalty and for increasing service usage.

Market expansion for organic food in India: assessing the consumers' attitude

Now a day's customers are more inclined towards a healthy lifestyle and consumption of organic food. The purpose of this paper is to comprehend the buyer intension to pay a higher price. This study focused on purchasing habit of customers towards organic food. Primary data of 500 respondents were collected from different areas of Punjab state of India in 2018. To calculate the results, descriptive statistics, multiple regression and factor analysis were used. Results of the research show that health and food safety are the two most important motives behind the intention to pay a higher price.

Market expansion for organic food in India: assessing the consumers' attitude

Now a day's customers are more inclined towards a healthy lifestyle and consumption of organic food. The purpose of this paper is to comprehend the buyer intension to pay a higher price. This study focused on purchasing habit of customers towards organic food. Primary data of 500 respondents were collected from different areas of Punjab state of India in 2018. To calculate the results, descriptive statistics, multiple regression and factor analysis were used. Results of the research show that health and food safety are the two most important motives behind the intention to pay a higher price.

Multi-Step Short-Term Power Consumption Forecasting Using Multi-Channel LSTM With Time Location Considering Customer Behavior

Short-Term Load Forecasting (STLF) is one critical assignment regarding the power supply and demand in the smart grid. Multi-step STLF provides strong evidence for decision-making to achieve consistent, quick supply and reduce direct or indirect cost. However, most of the current research only focuses on one-step STLF, which cannot satisfy the human-beings needs. Besides, short-term consumption fluctuates significantly in different periods and people, which increases the difficulty of forecasting. In this paper, we present a novel deep model named multi-channel long short-term memory (LSTM) with time location (TL-MCLSTM) in a multiple output strategy to forecast the multi-step short-term power consumption. The proposed model contains three channels: power consumption, time location, and customer behavior channels, respectively. Power consumption channel reflects the change and general trend of use; Time location channel reflects the hidden pattern of customer habits, which records the information consisting of time, day of the week, holidays. Moreover, we combine a convolution autoencoder and k-means to identify the type of behavior at the customer behavior channel. Power consumption and time location channels are trained individually through the LSTM as it has excellent memory function. Extracted features from LSTM in power consumption and time location channels are combined with customer behavior as comprehensive features to forecast. We designed, trained, and verified our proposed deep model on two nature data sets, and compared with other leading deep learning-based methods. The comparative studies have confirmed the effectiveness and priority of TL-MCLSTM for multi-step short-term consumption forecasting.

Predicting customer absence for automobile 4S shops: A lifecycle perspective

Repair and maintenance services are among the most lucrative aspects of the entire automobile business chain. However, in the context of fierce competition, customer churns have led to the bankruptcy of several 4S (sales, spare parts, services, and surveys) shops. In this regard, a six-year dataset is utilized to study customer behaviors to aid managers identify and retain valuable but potential customer churn through a customized retention solution. First, we define the absence and presence behaviors of customers and thereafter generate absence data according to customer habits; this makes it possible to treat the customer absence prediction problem as a classification problem. Second, the repeated absence and presence behaviors of customers are considered as a whole from a lifecycle perspective. A modified recurrent neural network (RNN-2L) is proposed; it is more efficient and reasonable in structure compared with traditional RNN. The time-invariant customer features and the sequential lifecycle features are handled separately; this provides a more sensible specification of the RNN structure from a behavioral interpretation perspective. Third, a customized retention solution is proposed.By comparing the proposed model with those that are conventional, it is found that the former outperforms the latter in terms of area under the curve (AUC), confusion matrix, and amount of time consumed. The proposed customized retention solution can achieve significant profit increase. This paper not only elucidates the customer relationship management in the automobile aftermarket (where the absence and presence behaviors are infrequently considered), but also presents an efficient solution to increase the predictive power of conventional machine learning models. The latter is achieved by considering behavioral and business perspectives.

Entity crisis, halo effect and loyalty

Taking as reference the period of deep financial and economic crisis suffered at global level, with special incidence in the Spanish financial industry, this paper examines the effect of entity crisis on consumer loyalty, studying the halo effect on trust, brand image and social norms. A causal model is proposed and contrasted with a sample of 500 bank customers and structural equation models were used to verify the hypothesized relationships. The contribution of this research is related to the analysis of the model proposed from a theoretical and empirical perspective. The general model establishes the consumption habits of customers during an entity crisis. It can be seen that the most important antecedent of loyalty are social norms, followed by trust and then brand image. However, the intensity of the crisis in each entity changes the results. The findings suggest that loyalty is an anti-cyclic strategy for firms. Investing in building customer loyalty in boom years generates positive credit towards the firm from customers who are unwilling to abandon it even when it is in crisis. The halo effect is fulfilled in the sense that customers’ general opinion of the entity and the more emotional variable determines and moderates negative news from the environment which attempts to influence consumers’ beliefs.

Created customer value by different trade formats of fast-moving consumer goods in Poland and Ukraine

<p><strong>Theoretical background</strong>: The main components of costumer value are the product, brand and image, personnel relationships and service activities, and offer availability. In retail, the important attributes of the products on sale are their range, price and terms of sale, relevant proximity and the benefit of obtaining, which includes spatial accessibility, emotional offer and time value. Modern trade solutions have created a wide range of opportunities for the client to facilitate access to the product offer through the introduction of various trading formats. The trade format should be understood as various concepts of retail outlet activity, which includes the formation of their infrastructure, immediate environment and the organisation of the sale of goods.</p><p><strong>Purpose of the article</strong>: The goal of the article is to classify the factors that create customer value using various formats of retail trade in consumer goods in the Ukrainian and Polish markets.</p><p><strong>Research methods</strong>: The following methods were used in this research: the abstract and logical method was used for generalising the theory and formulating conclusions; secondary research and survey were used for identifying the trends and patterns of efficiency in the studied factors; and the graphical method was used for visualising the results of the research.</p><p><strong>Main findings</strong>: In certain formats of sales points, the value for the customers is the breadth of the choice of goods and their quality, location and speed of purchase, the benefits arising from the level of prices and promotions, the service level and the general climate of the time offered by a store. The availability and possibility of goods choice has formed certain trends and customer habits among the buyers of consumer goods who are showing a preference for large purchases in hypermarkets and discount stores, supplementing purchases in specialised stores and only infrequently (in the Polish version) in markets/bazaars.</p>

Internet of things and smart warehouses as the future of logistics

Innovations and market changes in warehouse and logistics systems force the adaptation and transformation of the existing business model into a business model based on modern technology. With the development of the Internet, RFID (radio-frequency identification) technology and sensors, new innovations are being created that allow the improvement of the existing mode of activity. Implementation of the new technology brings along a number of challenges that organizations must find an adequate response to. However, warehouse systems are not the only affected by the new technologies. The development of technology and technological innovations enable organizations to develop sustainability. Sustainable development is imperative due to increasing awareness of the need for environmental protection. The supply chain can also be managed much more efficiently if sensors that collect information of customer habits and process performance are implemented. Given the accelerating development of Industry 4.0 and the opportunities offered by newly developed technology, this paper provides an overview of current developments in the implementation of Industry 4.0 technological innovations in logistics.

Opportunities and Challenges Addressing Access to Healthy Food in Five Rural Louisiana Food Stores.

The prevalence of high obesity in rural communities may result from low access to healthy foods. To improve the local food environment, a multicomponent environmental food store intervention was implemented in 3 Louisiana parishes where obesity prevalence was greater than 40%. The intervention consisted of healthy-food demonstrations, in-store marketing, and encouraging store owners to stock healthy items. We documented aspects of the rural food store climate, such as store size and the store owner’s willingness to stock healthy items, that affect improving access to healthy food. We found that although the intervention was not effective in shifting purchasing or dietary habits of customers, positive changes in some food store environments did occur. To maximize the effect that rural food store interventions can have on reducing obesity, it is essential to understand aspects of the rural food store climate.

VERNACULAR ARCHITECTURE: CHANGES IN THE TRADITION FOLKLORIC FORMS AND NARRATIONS IN OLD LEBANESE HOUSES

The vernacular houses have sustained our traditional habits and customs which were related to the way dwellers lived and adapted to the interior space of these houses. Although they share most of the essential characteristics, each house had its unique approach to details: location, orientation, kind of stones and woods, among many other basics used in the interior. These houses were built for a purpose, with the determination to create a shelter, to provide privacy and to establish a heaven within those thick walls ‘ kallin’ ; securing against danger, disaster and malicious attacks. In a gesture of written preservation to manuscript some types of old traditional houses still existing in the country side, namely in Achkout; my village in the heart of Keserwan, overlooking the Mediterranean Sea in Lebanon, I will document the few still-existing custom habits and household folkloric patterns and record old and bygone stories and rituals that are still in the memory of the very few elderlies who are still alive, in a sincere effort, I try to preserve Achkout’s identity and to create awareness legacy; to help in protecting my village identity and to resuscitate in the hearts and minds, the curiosity and mystery of the old folkloric spaces of the ‘once upon a time’ era. Needless to say, that after these transformations, the vernacular house is on the verge of losing all relations with the old heritage and traditional ways of construction; masonry work that undertook abundant group work; voluntary craftsmanship of helping hands; “ aouneh ”, to finish, is nowadays fading away. The “ aouneh ”, free exchanging aid between the villagers, that was the ritual way of living which established the profound bonding between the house, its dwellers and the rest of the village inhabitants. These architectural customs are being communicated now as mere competitive forms of complicated commercial entities built on random sites, spread along the country side, where the concept of “aouneh” ceases to exist. Concerning the folkloric structure in building and accessorizing, not one single house was similar to the other, even in the generals, such as tools and partitions; “outa-a ou aata-a” . Each detail in every house was directly related to the dwellers who characterized, personalized, and occupied the interior space to fulfil their necessities and daily needs. The unrestrained diffusion between the past and the present, the divergence and the intermixing between conventional customs and the old ethnic performances related to the folkloric masonry of interior spaces, could coexist.

Identifying the influencing factors of the sustainable energy transitions in China

This paper aims to explore the influencing factors that facilitate sustainable energy transitions in China. For this purpose, this paper assumes that the impact of the energy transition is from three main factors, energy technology innovations, the energy market, and socio-technical regimes, which can be subdivided into 11 subfactors. To empirically test the proposed hypotheses, questionnaire survey data collected from Chinese energy enterprises are statistically analysed by structural equation models (SEMs). The results show that, first, energy technology innovations, the energy market, and socio-technical regimes are the major forces in the transition to sustainable energy in China. Second, the effects of the three main factors on the energy transition vary according to 11 different subfactors. Some subfactors, i.e., innovation strategy, innovation factors, innovation policy, innovation network, and new energy competitiveness, have very important positive effects on the energy transition. Some subfactors, i.e., competitiveness of the coal industry, customer habits and coal-based infrastructure, have negative effects on the transition to sustainable energy in China. Third, the influence of the subfactors on the transition performance is diminished as a result of the joint intermediate effects of transition behaviours.

A study on organic foods purchase intention of Indian customers: a structural approach

Nowadays, customers are more interested toward a healthy way of life. They apprehend that the meals they are consuming have direct impact on their health and they are preferring organic food over the food prepared with the help of harmful chemicals. Indian population is showing a huge interest in the use of natural meals. It is very difficult for a businessman to know the changing buying habit of customers, so the current research is very useful to understand the affecting factors on the buying attitude of Indian organic food customers. This study proposed a research model and used a questionnaire to collect the data of 200 organic food users. The information evaluation has used confirmatory factor analysis (CFA) to establish validities of the instrument and in the process, identified that every indicating variable has meditated their primary constructs. After the CFA, it is described that the perfect fit for the statistics contemplated by the form of measurement. Path analysis approach was used to test the causal effect association with several constructs (structural model). The association ship model for buying intention may additionally assist the agency in dealing with the market for organic food.

A Case Study on BioChannel Partner: How Can the Sales Turnover of BioChannel Partners’ Online Services Be Increased?

Purpose: BioChannel Partners Ltd. (BCP) is a premier supplier of company matchmaking services in the Life Science industry that assists laboratory product suppliers to increase their export sales by identifying the best possible distributors. The study focuses on increment of the sales turnover of BioChannel Partners’ on-line business. Design/methodology/approach: The research is conducted in two phases: primary research and secondary research. The objective of both phases is to identify the reasons for the low sales of BioChannel Partners’ online services. Secondary research represents the first part of the research phase and includes an internal and external analysis of the company. Primary research involves a thorough study of the feedback collected from the primary research to reveal problem areas. The other objective is analysing what should be done to increase the sales turnover of the on-line services of BCP. This involves making recommendations for improvement based on the suggestions gathered from the customers directly through in-depth telephone interviews and online surveys. Findings: The results of the research phase have identified four major problem areas. First, there are prevailing customer habits of selecting distributors on a personal level via references and networking. Second, BCP’s on-line service Silver does not attract customers due to less value for money. Third, BCP only makes use of few market research to adjust product and pricing to customer preferences. Fourth, the benefits of the on-line services are not clearly communicated, whereas the web design confuses the issue even more. Originality/value: This paper provides BCP with a guideline to address its problems and increase its sales turnover by attracting and retaining more customers. These recommendations are relevant for most companies in this industry and can be utilised to improve the functioning of the organization.

Bayesian Item Response Analysis of Method-of-Payment Habits in Banking Surveys

Customers have a wide variety of choices in selecting a method of payment in modern society due to advancements in technology. In this paper, we investigate the method of payment habits of banking customers using item response models. We consider three binary item response models used in the literature within the Bayesian framework. These models capture the heterogeneity and complexity of customer perception on methods of payment in different capacities, with different features. For this reason, model assessment methods need to be developed for better inferential purposes. We introduce an assessment criterion based on predictive simulations and illustrate the approach using graphical summary measures. The approach is further highlighted using survey data based on consumer payment choices that was conducted for the Federal Reserve Bank of Boston.

Upacara Kematian dalam Tradisi suku Toraja dalam Novel Puya ke Puya Karya Faisal Oddang: Kajian Sosiologi Sastra

The object of this study is novel Puya ke Puya by Faisal Oddang. Novel Puya ke Puya is analyzed using the theory of structure and the theory of sociology of literature. The using of sociologyof literature theory in this study is appropriate because the novel Puya ke Puya has a strong social view on the characters. The problems discussed are structural and social aspects of the Toraja contained in the novel Puya ke Puya. The structure of novel Puya ke Puya, include: characterization, plot and setting. Characterizations are divided into the main character and an additional character, the main character is Allu Ralla, additional characters are Rante Ralla, Tina Ralla, Malena, Maria Ralla, Mr. Berth, Mr. Soso and the Village Head. The plot of novel Puya ke Puya is chronological. Then the setting of place in novel Puya ke Puya is located in South Sulawesi Island, setting of time is in 2010, and the social background tell the life of the Toraja people. The social aspect of the Toraja in the novel Puya ke Puya, covering the economic, religious and cultural aspects. The economic aspect uncover the Toraja prosperity problems in society. The religious aspect explains the trust that connect people with the order of life. The cultural aspect explains the matters of custom and community habits.

Attended Home Delivery: reducing last-mile environmental impact by changing customer habits

Frequently, e-commerce customers pay additional costs for home delivery taking place in a restricted time window. We show how such a behavior is counterproductive in terms of last-mile routing operations. We consider two typical retailer policies to organize the service (a fast delivery in a restricted time interval or the presence of different time windows for each customer) and model them as optimization problems that minimize traveled distance as main cost source for the retailer. For both problems, we convert the obtained number of kilometers into gas emissions under different scenarios characterized by different time windows width. Results are extremely interesting, indicating more sustainable e-commerce customer-oriented strategies.

Cold chain interruption by consumers significantly reduces shelf life of vacuum-packed pork ham slices

The spoilage of meat products (N>5×106 CFU g−1) can be delayed by cooling and low-temperature storage and transport. The highest extent of interruption in the cold chain occurs at the time of delivering the meat product to the individual’s home after purchasing it. Consumer behaviour and the ambient temperature largely influence the shelf life of products. In our research, we examined the buying habits of customers in Hungary. Based on these results, we carried out the cold chain interruption of vacuum-packed sliced ham (1, 2, 3 h) under laboratory conditions, at temperatures of 15, 25, and 35 °C. The microbial count was determined by a quick method based on redox-potential measurement in two-three days until the products were deteriorated. Our experiments resulted in the expected outcomes; however, we concluded that even average customer habits (1 h cold chain interruption) at higher temperature periods (T>20 °C) decrease the shelf life of ham by 6 days. We set up a mathematical model through which the changes of microbial counts can be determined as a function of product temperature changes, the period of delivery, and the subsequent period of cold storage. R2=0.9 correlation was given between predicted and measured microbial counts (logN).

Transparent password policies: A case study of investigating end-user situational awareness

Loyalty of customers to a supermarket can be measured in a variety of ways. If a customer tends to buy from certain categories of products, it is likely that the customer is loyal to the supermarket. Another indication of loyalty is based on the tendency of customers to visit the supermarket over a number of weeks. Regular visitors and spenders are more likely to be loyal to the supermarket. Neither one of these two criteria can provide a complete picture of customers’ l The decision regarding the loyalty of a customer will have to take into account the visiting pattern as well as the categories of products purchased. This paper describes results of experiments that attempted to identify customer loyalty using thes e two sets of criteria separately. The experiments were based on transactional data obtained from a supermarket data collection program. Comparisons of results from these parallel sets of experiments were useful in fine tuning both the schemes of estimating the degree of loyalty of a customer. The project also provides useful insights for the development of more sophisticated measures for studying customer loyalty. It is hoped that the understanding of loyal customers will be helpful in identifying better marketing strategies. 1. Introductionloyalty is an important component of marketing analysis in a supermarket. The loyalty of a customer may be apparent through the products bought by the customer. Certain product categories such as bread and eggs may have a higher ability to distinguish between loyal and disloyal customers. Other product categories such as coffee/tea and ketchup may not be deterministic of a customer’s loyalty but may simply enhance their degree of loyalty. Establishing a scoring system based on such key product categories is one possible way of determining customer loyalty. However, the dietary habits of some loyal customers may lead to lower loyalty scores if they are based solely on product categories. Studying patterns in tra nsactional records can also provide important clues about the loyal patrons of the supermarket. It is important to conduct parallel analyses of products purchased and transaction patterns for identifying loyal customers. The two separate analyses can also be used for fine-tuning each other. This paper reports the results of experiments that studied various characteristics of loyal customers based on the products purchased and visiting patterns. The experiments were based on the data obtained from a large national supermarket chain, which was gathered over a thirteen-week period in 2000. The project was divided into two parallel streams: product based and transaction pattern based analyses. The product based analysis started with a preliminary definition of loyal customers, based on spending levels. 1 The authors would like to thank NSERC Canada, the Nova Scotia Cooperative Employment Program, and the Senate Research Grant Committee of Saint Mary’s University for the financial support. The authors are also grateful to the supermarket chain and it’s management for allowing us the use of the data.

Data granularity enhancements in Google Analytics to better understand visitor behaviour

In recent years, Google Analytics has become the most important data analytics tool of the trade for marketing managers, e-commerce specialists, search engine optimisation consultants and webmasters worldwide. For the marketing analyst, however, the tool also has clear limitations, as it is impossible to obtain direct access to its database, which contains the data gathered to provide the reports with which everyone is familiar. Nonetheless, it is possible to increase the granularity of the data using a few lines of JavaScript code. This code is used to replicate part of the logic of the Google Analytics database and to access the underlying data needed to generate more elaborate statistics and, thus, acquire crucial information on the purchasing behaviours and habits of customers and users online.